Triple
T37117801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor (India) |
E919163
|
entity |
| Predicate | canBeGovernorOf |
P198816
|
FINISHED |
| Object | more than one 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: more than one state | Statement: [Governor (India), canBeGovernorOf, more than one state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeGovernorOf Context triple: [Governor (India), canBeGovernorOf, more than one state]
-
A.
hasRankOfGovernor
Indicates that an entity holds the official position or rank of governor in relation to a specified jurisdiction or organization.
-
B.
governorateOf
Indicates that one entity is the governorate (administrative region) to which another entity belongs or is located within.
-
C.
hasGovernorPer
Indicates that a person serves as the governor of a particular political or administrative entity.
-
D.
wonGovernorshipIn
Indicates that an entity achieved victory in an election or contest to become the governor of a specified region or jurisdiction.
-
E.
stateOfGovernorship
Indicates the relationship in which an individual holds or held the official position and authority of governor over a specific jurisdiction.
- F. None of above. chosen
Provenance (4 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff0b6bc4a88190bf1d38c6ea26bcdc |
completed | May 9, 2026, 10:24 a.m. |
| PD | Predicate disambiguation | batch_69ff082a22f4819095ded971dbd8ea7b |
completed | May 9, 2026, 10:10 a.m. |
| PDg | Predicate description generation | batch_69ff0b6a541c8190a6fa847552f3491f |
completed | May 9, 2026, 10:24 a.m. |
Created at: May 3, 2026, 4:15 p.m.