Triple
T15528472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nayarit |
E369143
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Tepic |
E173358
|
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: Tepic | Statement: [Nayarit, capital, Tepic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tepic Context triple: [Nayarit, capital, Tepic]
-
A.
Tepic
chosen
Tepic is the capital city of the Mexican state of Nayarit, known as a regional commercial and transportation hub in western Mexico.
-
B.
Yautepec
Yautepec is a municipality in the Mexican state of Morelos known for its warm climate, agriculture, and growing tourism and residential developments.
-
C.
Tepatitlán de Morelos
Tepatitlán de Morelos is a prominent city in Mexico known for its agricultural production, religious traditions, and vibrant regional culture.
-
D.
Zacatepec
Zacatepec is a Mexican professional football club historically known for competing in the country's top divisions and developing notable players.
-
E.
Tulancingo
Tulancingo is a historic city in central Mexico known for its colonial architecture, regional commerce, and cultural traditions within the state of Hidalgo.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0414620588190958ffde651ccab5f |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3b205dc81908c4194a931d94074 |
completed | May 9, 2026, 11:30 p.m. |
Created at: April 10, 2026, 4:05 a.m.