Triple
T9524090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of Puebla |
E229715
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Atlixco |
E347762
|
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: Atlixco | Statement: [State of Puebla, hasMajorCity, Atlixco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atlixco Context triple: [State of Puebla, hasMajorCity, Atlixco]
-
A.
Atlixco
chosen
Atlixco is a historic city in the Mexican state of Puebla, known for its vibrant crafts tradition, flower production, and colonial architecture.
-
B.
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.
-
C.
Tezoyuca
Tezoyuca is a municipality in the State of Mexico, known for its location in the central Mexican plateau and its blend of rural traditions with growing urban development.
-
D.
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).
-
E.
Cadereyta Jiménez
Cadereyta Jiménez is a municipality in the Mexican state of Nuevo León, known for its oil refinery and agricultural activities within the Monterrey metropolitan area.
- 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_69ca847870a881909d8d751a7d29da39 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9899f99481908d374528716027f8 |
completed | April 1, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d178eb63e08190b069faaa0c5dbcb2 |
completed | April 4, 2026, 8:47 p.m. |
Created at: March 30, 2026, 7:59 p.m.