Triple
T6884985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creel station |
E158895
|
entity |
| Predicate | hasService |
P182
|
FINISHED |
| Object | Chepe Regional |
E625983
|
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: Chepe Regional | Statement: [Creel station, hasService, Chepe Regional]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chepe Regional Context triple: [Creel station, hasService, Chepe Regional]
-
A.
Chepe
chosen
Chepe is a scenic Mexican passenger train service that runs through the Copper Canyon region in the state of Chihuahua.
-
B.
Cucunubá
Cucunubá is a small colonial-era town in the Cundinamarca department of Colombia, known for its traditional wool textiles and scenic Andean highland landscapes.
-
C.
Copiapó Province
Copiapó Province is an administrative division in northern Chile known for its mining activities and desert landscapes, including parts of the Atacama Desert.
-
D.
Chacala
Chacala is a small coastal village and beach destination on Mexico’s Pacific coast in the state of Nayarit, known for its tranquil atmosphere, surfing, and ecotourism.
-
E.
Bajío
Bajío is a fertile, economically important region in central-western Mexico known for its agriculture, industry, and colonial cities.
- 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_69c688342f6c8190ad7eea6ba262db99 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d90a2590819092ff253dd66ebe8b |
completed | March 27, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748cc2f908190b593cd82133a7b16 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:23 p.m.