Triple
T13714295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asientos |
E328852
|
entity |
| Predicate | hasMunicipalSeat |
P1474
|
FINISHED |
| Object | Asientos |
E328852
|
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: Asientos | Statement: [Asientos, hasMunicipalSeat, Asientos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asientos Context triple: [Asientos, hasMunicipalSeat, Asientos]
-
A.
Asientos
chosen
Asientos is a historic mining town and municipality in the northeastern part of the Mexican state of Aguascalientes.
-
B.
The Chairs
The Chairs is a seminal absurdist play by Eugène Ionesco that portrays an elderly couple preparing an ever-growing number of empty chairs for invisible guests in a bleak, existential farce.
-
C.
The Chair
The Chair is a television series best known as a satirical drama about the challenges facing the first woman of color to chair a struggling university English department.
-
D.
The Chair
"The Chair" is a classic 1985 country ballad by George Strait, known for its clever conversational lyrics and status as one of his signature hits.
-
E.
The Chair
The Chair is one of the most famous and challenging fences in the Grand National steeplechase at Aintree Racecourse, known for its size and difficulty.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd43973cf08190a417d0cca9dd314a |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a847c4d08190b05ea525059f0465 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:54 p.m.