Triple
T3965235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2 (O'Hare) |
E92201
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
T2
T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
|
E402725
|
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: T2 | Statement: [Terminal 2 (O'Hare), alsoKnownAs, T2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T2 Context triple: [Terminal 2 (O'Hare), alsoKnownAs, T2]
-
A.
T2
T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
-
B.
T2
T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
-
C.
T2
T2 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
-
D.
T2
T2 is a Sydney Trains suburban rail service designation used for the Inner West & Leppington Line in the Sydney metropolitan network.
-
E.
T3
T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
- 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: T2 Triple: [Terminal 2 (O'Hare), alsoKnownAs, T2]
Generated description
T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T2 Target entity description: T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
-
A.
T2
T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
-
B.
T2
T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
-
C.
T2
T2 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
-
D.
T2
T2 is a Sydney Trains suburban rail service designation used for the Inner West & Leppington Line in the Sydney metropolitan network.
-
E.
T3
T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef97520588190922e56201fc3ca52 |
completed | March 9, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533be4a688190a7d011ae2858e6ed |
completed | March 14, 2026, 10:09 a.m. |
| NEDg | Description generation | batch_69b537cc86e88190bae10e740d8c3ec7 |
completed | March 14, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b538595d2481908812ab03cdb94659 |
completed | March 14, 2026, 10:28 a.m. |
Created at: March 9, 2026, 3:31 p.m.