Triple
T7759154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toledo Express Airport |
E175973
|
entity |
| Predicate | FAAcode |
P420
|
FINISHED |
| Object | TOL |
E687019
|
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: TOL | Statement: [Toledo Express Airport, FAAcode, TOL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TOL Context triple: [Toledo Express Airport, FAAcode, TOL]
-
A.
TOL
TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
-
B.
TOL
chosen
TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
-
C.
TLO
TLO, also known as Dario Wünsch, is a German professional StarCraft II player renowned for his creative strategies and long-standing presence in the competitive scene.
-
D.
Toller
Toller is a supporting character in the 1966 Western film "Duel at Diablo," set against the backdrop of frontier conflict between U.S. cavalry and Apache forces.
-
E.
CO-TOL
CO-TOL is the ISO 3166-2 code that uniquely identifies Colombia’s Tolima Department in international and administrative contexts.
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703de43d08190ac28bc17cd3e5ffa |
completed | March 27, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8d6c06f54819096162e84180918ba |
completed | March 29, 2026, 7:37 a.m. |
Created at: March 27, 2026, 4:09 p.m.