Triple
T19560435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Highway 45 |
E489433
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Celaya |
—
|
NE NERFINISHED |
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: Celaya | Statement: [Federal Highway 45, connectsCity, Celaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Celaya Context triple: [Federal Highway 45, connectsCity, Celaya]
-
A.
Celaya
chosen
Celaya is a major city and industrial municipality in the Mexican state of Guanajuato, known for its manufacturing sector and traditional cajeta (goat’s milk caramel).
-
B.
Monclova
Monclova is an industrial city in northern Mexico known as a major steel-producing center in the state of Coahuila.
-
C.
Irapuato
Irapuato is a city in the Mexican state of Guanajuato known for its agricultural production, especially strawberries, and its role as an important regional economic center.
-
D.
Irapuato
Irapuato is a Mexican professional football club based in the city of Irapuato, Guanajuato, known for its passionate fan base and history in the country’s lower divisions.
-
E.
Xalapa
Xalapa is a city in eastern Mexico known as the capital and cultural center of the state of Veracruz.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f731ae48190ade295c15db7f8ed |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.