Triple
T14471965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dijon tramway |
E358866
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
T1
T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
|
E1100239
|
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 | Statement: [Dijon tramway, hasLine, T1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T1 Context triple: [Dijon tramway, hasLine, T1]
-
A.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
B.
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.
-
C.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
T2
T2 is a Sydney Trains suburban rail service designation used for the Inner West & Leppington Line in the Sydney metropolitan network.
- 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 Triple: [Dijon tramway, hasLine, T1]
Generated description
T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T1 Target entity description: T1 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit across key parts of the city.
-
A.
T1
T1 is one of the tram routes of the Trambaix light rail network serving the Barcelona metropolitan area.
-
B.
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.
-
C.
T1
T1 is a tram line serving the Lyon metropolitan area in France, connecting key districts including Villeurbanne.
-
D.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
E.
T2
T2 is a Sydney Trains suburban rail service designation used for the Inner West & Leppington Line in the Sydney metropolitan network.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91fab21c819090b6e209d8efba6e |
completed | April 14, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd649e103c81908001b45c16d1fd79 |
completed | May 8, 2026, 4:20 a.m. |
| NEDg | Description generation | batch_69fd658f2c1c8190b6a564dbe75fc2f2 |
completed | May 8, 2026, 4:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd661c201c8190ba8ce1295849e8c1 |
completed | May 8, 2026, 4:27 a.m. |
Created at: April 10, 2026, 1:20 a.m.