Triple
T18202946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guerrero region |
E435834
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Chilpancingo de los Bravo |
—
|
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: Chilpancingo de los Bravo | Statement: [Guerrero region, hasCity, Chilpancingo de los Bravo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chilpancingo de los Bravo Context triple: [Guerrero region, hasCity, Chilpancingo de los Bravo]
-
A.
Chilpancingo
Chilpancingo is a Mexico City Metro station on Line 9 located in the central area of the city, serving neighborhoods such as Colonia Condesa and Roma.
-
B.
Chilpancingo
chosen
Chilpancingo is a city in southern Mexico that serves as the capital of the state of Guerrero and played a key role in the country’s independence movement.
-
C.
Celaya
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).
-
D.
Xalapa
Xalapa is a city in eastern Mexico known as the capital and cultural center of the state of Veracruz.
-
E.
Yautepec
Yautepec is a municipality in the Mexican state of Morelos known for its warm climate, agriculture, and growing tourism and residential developments.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e220dca48190b54dabbd3c7c99b7 |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.