Triple
T28361006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NTR district |
E718360
|
entity |
| Predicate | namedAfterPersonPoliticalRole |
P16867
|
FINISHED |
| Object | Chief Minister of Andhra Pradesh |
—
|
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: Chief Minister of Andhra Pradesh | Statement: [NTR district, namedAfterPersonPoliticalRole, Chief Minister of Andhra Pradesh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterPersonPoliticalRole Context triple: [NTR district, namedAfterPersonPoliticalRole, Chief Minister of Andhra Pradesh]
-
A.
namedForPoliticalRole
chosen
Indicates that one entity is named after another entity specifically because of that entity’s political office, position, or role.
-
B.
namedAfterOfficeholder
Indicates that one entity is named in honor of, or derived from the name of, a person who has held a particular public or official office.
-
C.
namedPersonRole
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
D.
namedAfterCountryLeaderOf
Indicates that one entity is named after a person who is or was the leader of a specific country.
-
E.
notableOfficeHolder
Indicates that an entity is a significant or distinguished holder of a particular office or position associated with another entity.
- 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_69eff6ed5af48190be4e0adf298223e0 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 28, 2026, 12:52 a.m.