Triple
T10991576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hausdorff space |
E259764
|
entity |
| Predicate | isStrongerThan |
P2373
|
FINISHED |
| Object |
T1 separation axiom
The T1 separation axiom is a topological property requiring that for any two distinct points, each has an open set containing it but not the other, ensuring all singletons are closed.
|
E898480
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: T1 separation axiom | Statement: [Hausdorff space, isStrongerThan, T1 separation axiom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T1 separation axiom Context triple: [Hausdorff space, isStrongerThan, T1 separation axiom]
-
A.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
B.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
-
C.
T1
T1 is one of the main tram lines in Casablanca’s urban light rail network, providing mass transit service across key districts of the city.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
T2-SE-A1
T2-SE-A1 is a World War II–era American oil tanker design, built in large numbers for the U.S. Maritime Commission as a standard T2-class ship used to transport fuel across the oceans.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: T1 separation axiom Triple: [Hausdorff space, isStrongerThan, T1 separation axiom]
Generated description
The T1 separation axiom is a topological property requiring that for any two distinct points, each has an open set containing it but not the other, ensuring all singletons are closed.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T1 separation axiom Target entity description: The T1 separation axiom is a topological property requiring that for any two distinct points, each has an open set containing it but not the other, ensuring all singletons are closed.
-
A.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
B.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
-
C.
T1
T1 is one of the main tram lines in Casablanca’s urban light rail network, providing mass transit service across key districts of the city.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
T2-SE-A1
T2-SE-A1 is a World War II–era American oil tanker design, built in large numbers for the U.S. Maritime Commission as a standard T2-class ship used to transport fuel across the oceans.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d1e918819090c71f5a077fa15a |
completed | April 9, 2026, 12:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e34504ebec8190a78e4795765b0c24 |
completed | April 18, 2026, 8:47 a.m. |
| NEDg | Description generation | batch_69e3556fd3548190a33f04604be947cf |
completed | April 18, 2026, 9:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3593b0f8481909ed7a90f8bb9839d |
completed | April 18, 2026, 10:13 a.m. |
Created at: April 8, 2026, 9:24 p.m.