Triple
T6681387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airside F |
E151988
|
entity |
| Predicate | IATAAirport |
P2569
|
FINISHED |
| Object | TPA |
E151982
|
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: TPA | Statement: [Airside F, IATAAirport, TPA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TPA Context triple: [Airside F, IATAAirport, TPA]
-
A.
TPA
chosen
TPA is the three-letter IATA airport code for Tampa International Airport, a major commercial airport serving the Tampa Bay area in Florida, USA.
-
B.
TPA
TPA is an abbreviation commonly used for a Tri-Party Agreement, a legal contract involving three separate parties that defines their respective rights and obligations.
-
C.
TAP
TAP is the ICAO airline designator for TAP Air Portugal, the flag carrier airline of Portugal.
-
D.
TAP
TAP is a reusable smart fare card system used for paying transit fares across multiple public transportation agencies in the Los Angeles County area.
-
E.
TAA
TAA is the stock ticker symbol for Tandberg, a Norwegian company known for its video conferencing and telecommunication solutions.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b11f945481908e1a9f0839c35b5b |
completed | March 27, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71290084081909f23126c63d2d2ab |
completed | March 27, 2026, 11:28 p.m. |
Created at: March 27, 2026, 2:04 p.m.