Triple
T5750588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tweed New Haven Airport |
E126841
|
entity |
| Predicate | pushpinMapRegion |
P33924
|
FINISHED |
| Object | USA |
E391575
|
NE FINISHED |
How this triple was built (2 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: USA | Statement: [Tweed New Haven Airport, pushpinMapRegion, USA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USA Context triple: [Tweed New Haven Airport, pushpinMapRegion, USA]
-
A.
USA
USA is a public research university located in Mobile, Alabama, known for its diverse academic programs and regional impact in the Gulf Coast area.
-
B.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
-
C.
US
chosen
The US, or United States, is a large federal republic in North America composed of 50 states and known as one of the world's most influential economic and political powers.
-
D.
US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
-
E.
US
US is the commonly used abbreviation for the University of Seville, a major public research university located in Seville, Spain.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288a0ea8819091ac6f965471ceee |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16e75b76c8190881ce6ec2d093925 |
completed | March 23, 2026, 4:46 p.m. |
Created at: March 22, 2026, 3:48 p.m.