Triple
T892385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2 (San Francisco International Airport) |
E19268
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
T2
T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
|
E105943
|
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 (San Francisco International Airport), alsoKnownAs, T2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T2 Context triple: [Terminal 2 (San Francisco International Airport), alsoKnownAs, T2]
-
A.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
B.
T5
T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
-
C.
TB
TB is the standard abbreviation for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
-
D.
A22
A22 is a major Portuguese motorway, commonly known as Via do Infante, that runs across the Algarve region in southern Portugal.
-
E.
TC
TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
- 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 (San Francisco International Airport), alsoKnownAs, T2]
Generated description
T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: T2 Target entity description: T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
-
A.
the T
The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
-
B.
T5
T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
-
C.
TB
TB is the standard abbreviation for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
-
D.
A22
A22 is a major Portuguese motorway, commonly known as Via do Infante, that runs across the Algarve region in southern Portugal.
-
E.
TC
TC is the standard abbreviation for the IEEE Transactions on Computers, a leading peer-reviewed journal covering research in computer science and engineering.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0304b081908d4c92bb2beadb81 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c025464081908032939637248635 |
completed | March 4, 2026, 5:16 a.m. |
| NEDg | Description generation | batch_69a7c227893c8190a4ce35637365014f |
completed | March 4, 2026, 5:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c2f1d0508190ad47eeb8099fd9f9 |
completed | March 4, 2026, 5:28 a.m. |
Created at: March 1, 2026, 7:39 p.m.