Triple
T10573508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Costa Grande region |
E249551
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Petatlán |
E878245
|
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: Petatlán | Statement: [Costa Grande region, hasMunicipality, Petatlán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petatlán Context triple: [Costa Grande region, hasMunicipality, Petatlán]
-
A.
Petatlán
chosen
Petatlán is a town and municipality in the Mexican state of Guerrero, known for its agricultural production and proximity to the Pacific coast.
-
B.
Tototlán
Tototlán is a municipality and town in the Mexican state of Jalisco, known for its agricultural economy and traditional regional culture.
-
C.
Tejutla
Tejutla is a municipality located in the highland region of western Guatemala, known for its rural communities and traditional agricultural activities.
-
D.
Metztitlán
Metztitlán is a town and municipality in the state of Hidalgo, Mexico, known for its dramatic canyon landscapes, rich biodiversity, and the nearby Metztitlán Biosphere Reserve.
-
E.
Tezonco
Tezonco is a metro station in Mexico City that serves the southeastern area of the city on the capital’s rapid transit network.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5274929cc81909a79d5e2049f7389 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9988fca088190b13b651985677a6a |
completed | April 11, 2026, 12:40 a.m. |
Created at: April 6, 2026, 12:37 p.m.