Triple
T36511870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E. S. L. Narasimhan |
E899928
|
entity |
| Predicate | officeAssumedAsGovernorOfTelangana |
P201821
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [E. S. L. Narasimhan, officeAssumedAsGovernorOfTelangana, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeAssumedAsGovernorOfTelangana Context triple: [E. S. L. Narasimhan, officeAssumedAsGovernorOfTelangana, 2014]
-
A.
officeAssumedAsGovernorOfAndhraPradesh
Indicates that an entity has taken up or begun serving in the official role of Governor of Andhra Pradesh.
-
B.
predecessorAsGovernorOfTelangana
Indicates that one person previously held the office of Governor of Telangana immediately before another person.
-
C.
officeAssumedAsGovernorOfWestBengalOn
Indicates the date on which an individual formally assumed the office of Governor of West Bengal.
-
D.
predecessorAsGovernorOfAndhraPradesh
Indicates that one entity previously held the position of Governor of Andhra Pradesh immediately before another entity.
-
E.
officeAssumedAsLieutenantGovernor
Indicates that an individual has formally taken on and begun serving in the role of lieutenant governor.
- 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_69f76e5dada881909da2d34bc7a9202a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a00262d71488190a769783fb09e5803 |
completed | May 10, 2026, 6:31 a.m. |
| PD | Predicate disambiguation | batch_6a0023985f148190a335a3fb93e9981e |
completed | May 10, 2026, 6:20 a.m. |
| PDg | Predicate description generation | batch_6a00262cc9408190b95076a2d3da057d |
completed | May 10, 2026, 6:31 a.m. |
Created at: May 3, 2026, 4:10 p.m.