Triple
T19556806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acolhua region |
E489334
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Huexotla |
—
|
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: Huexotla | Statement: [Acolhua region, majorCity, Huexotla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huexotla Context triple: [Acolhua region, majorCity, Huexotla]
-
A.
Huexotla
chosen
Huexotla was a pre-Columbian Mesoamerican city-state in the Valley of Mexico that played a role in regional conflicts such as the Tepanec War.
-
B.
Huixtla
Huixtla is a municipality and commercial town in the Soconusco region of Chiapas, Mexico, known for its agricultural production and regional trade.
-
C.
Mexicaltzingo
Mexicaltzingo is a Mexico City Metro station on Line 12 serving the Mexicaltzingo neighborhood in the eastern part of the city.
-
D.
Tepalcingo
Tepalcingo is a town in the Mexican state of Morelos known for its colonial-era church and annual religious fair that attracts thousands of pilgrims.
-
E.
Xilitla
Xilitla is a picturesque town in the Huasteca region of San Luis Potosí, Mexico, known for its lush mountainous landscape and its association with surrealist art and architecture.
- 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_69e63d341d708190b8ef35822f8bfe7c |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:42 p.m.