Triple
T36511871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E. S. L. Narasimhan |
E899928
|
entity |
| Predicate | officeLeftAsGovernorOfTelangana |
P201835
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [E. S. L. Narasimhan, officeLeftAsGovernorOfTelangana, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeLeftAsGovernorOfTelangana Context triple: [E. S. L. Narasimhan, officeLeftAsGovernorOfTelangana, 2019]
-
A.
officeAssumedAsGovernorOfTelangana
Indicates the event or state in which an individual formally assumes the office of Governor of Telangana.
-
B.
officeAssumedAsGovernorOfAndhraPradesh
Indicates that an entity has taken up or begun serving in the official role of Governor of Andhra Pradesh.
-
C.
predecessorAsGovernorOfTelangana
Indicates that one person previously held the office of Governor of Telangana immediately before another person.
-
D.
predecessorAsGovernorOfAndhraPradesh
Indicates that one entity previously held the position of Governor of Andhra Pradesh immediately before another entity.
-
E.
officeHeldAsGovernor
Indicates that an entity holds or has held the official position of governor of a political or administrative region.
- 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_6a0027e4a59481909417b2531daaf480 |
completed | May 10, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a0026a42bc08190ad3322ce625a523a |
completed | May 10, 2026, 6:33 a.m. |
| PDg | Predicate description generation | batch_6a0027e384d08190ad92a6a21c8f84b5 |
completed | May 10, 2026, 6:38 a.m. |
Created at: May 3, 2026, 4:10 p.m.