Triple
T16542003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PŁ |
E401839
|
entity |
| Predicate | hasAcronym |
P43
|
FINISHED |
| Object | TUL |
E739361
|
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: TUL | Statement: [PŁ, hasAcronym, TUL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TUL Context triple: [PŁ, hasAcronym, TUL]
-
A.
TUL
chosen
TUL is the three-letter IATA airport code for Tulsa International Airport, a commercial and military airfield serving Tulsa, Oklahoma.
-
B.
Tule
Tule are an Indigenous people of Panama and Colombia, also known as the Guna or Kuna, recognized for their autonomous island communities and vibrant textile art called molas.
-
C.
TOL
TOL is the standard abbreviation for the Toledo Walleye, a professional minor league ice hockey team based in Toledo, Ohio.
-
D.
TOL
TOL is the IATA airport code for Toledo Express Airport, a public airport serving the Toledo, Ohio area in the United States.
-
E.
Tulunan
Tulunan is a rural municipality in the province of North Cotabato on the island of Mindanao in the Philippines, known primarily for its agricultural economy.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3455db6788190b929546050ea2488 |
completed | April 18, 2026, 8:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067b0e5708190a286b8a316d6efd2 |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 10, 2026, 5:15 a.m.