Triple
T433246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Mexico |
E9757
|
entity |
| Predicate | includesSubdivisionType |
P9832
|
FINISHED |
| Object | state |
—
|
LITERAL 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: state | Statement: [Government of Mexico, includesSubdivisionType, state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesSubdivisionType Context triple: [Government of Mexico, includesSubdivisionType, state]
-
A.
hasSubdivision
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
B.
countrySubdivisionType
chosen
Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
-
C.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
D.
subdivisionRank
Indicates the hierarchical level or type of administrative or territorial subdivision that an entity occupies within a larger organizational or geographic structure.
-
E.
includesStateOrProvince
Indicates that one entity geographically contains or encompasses a specific state or province within its boundaries.
- F. None of above.
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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ef084840819080653004b674cba8 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2edda55e88190b7c17ba94d7df1ce |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.