Triple
T6830675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Escuinapa |
E157128
|
entity |
| Predicate | hasMunicipalSeat |
P1474
|
FINISHED |
| Object | Escuinapa de Hidalgo |
E157128
|
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: Escuinapa de Hidalgo | Statement: [Escuinapa, hasMunicipalSeat, Escuinapa de Hidalgo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Escuinapa de Hidalgo Context triple: [Escuinapa, hasMunicipalSeat, Escuinapa de Hidalgo]
-
A.
Escuinapa
chosen
Escuinapa is a coastal municipality and town in southern Sinaloa, Mexico, known for its fishing, agriculture, and shrimp farming.
-
B.
Apatlaco
Apatlaco is a Mexico City Metro station on Line 8 serving the Iztapalapa borough in the eastern part of the city.
-
C.
Zacahuitzco
Zacahuitzco is a neighborhood located within the Benito Juárez borough of Mexico City.
-
D.
Amatlán de Cañas
Amatlán de Cañas is a small municipality and town in the southern part of the Mexican state of Nayarit, known for its mountainous terrain, hot springs, and traditional rural character.
-
E.
Chimalhuacán
Chimalhuacán is a densely populated urban municipality in the eastern part of the State of Mexico, forming part of the Mexico City metropolitan area.
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d62820808190ad3c244893e88699 |
completed | March 27, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7426b3d2081909d0804a2fbc6efad |
completed | March 28, 2026, 2:52 a.m. |
Created at: March 27, 2026, 2:18 p.m.