Triple
T458695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico Time Zones |
E7287
|
entity |
| Predicate | includesRegion |
P285
|
FINISHED |
| Object | Guerrero |
E50767
|
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: Guerrero | Statement: [Mexico Time Zones, includesRegion, Guerrero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guerrero Context triple: [Mexico Time Zones, includesRegion, Guerrero]
-
A.
Guerrero
chosen
Guerrero is a coastal state in southwestern Mexico known for its mountainous terrain, including part of the Sierra Madre del Sur, and popular tourist destinations such as Acapulco.
-
B.
Hidalgo
Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
-
C.
Navarro
Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
-
D.
Anzures
Anzures is an upscale residential and commercial neighborhood in Mexico City known for its central location, embassies, and proximity to major business and cultural districts.
-
E.
Jaruco
Jaruco is a municipality in western Cuba known for its historic town and the nearby Jaruco Escalante hills and parklands.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa4a6208190a8243a0e14f84f52 |
completed | Feb. 28, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a457fed1548190b50d72886828b650 |
completed | March 1, 2026, 3:15 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.