Triple
T7669475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estadio Omnilife |
E173711
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Zapopan |
E228636
|
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: Zapopan | Statement: [Estadio Omnilife, locatedIn, Zapopan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zapopan Context triple: [Estadio Omnilife, locatedIn, Zapopan]
-
A.
Zapopan
chosen
Zapopan is a major city in western Mexico known as part of the Guadalajara metropolitan area and for its significant commercial, industrial, and religious importance.
-
B.
Tepic
Tepic is the capital city of the Mexican state of Nayarit, known as a regional commercial and transportation hub in western Mexico.
-
C.
Toluca
Toluca is a major city and the capital of the State of Mexico, known for its high altitude, industrial activity, and proximity to the Nevado de Toluca volcano.
-
D.
Tepatitlán de Morelos
Tepatitlán de Morelos is a prominent city in Mexico known for its agricultural production, religious traditions, and vibrant regional culture.
-
E.
Atlixco
Atlixco is a historic city in the Mexican state of Puebla, known for its vibrant crafts tradition, flower production, and colonial architecture.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701c5538881908139881daf41151a |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8a22442dc8190a26c966e7b06f1a9 |
completed | March 29, 2026, 3:53 a.m. |
Created at: March 27, 2026, 4 p.m.