Triple
T13068632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nimarata Nikki Randhawa |
E329394
|
entity |
| Predicate | officeEndTime (Governor of South Carolina) |
P63787
|
FINISHED |
| Object | 2017-01-24 |
—
|
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: 2017-01-24 | Statement: [Nimarata Nikki Randhawa, officeEndTime (Governor of South Carolina), 2017-01-24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeEndTime (Governor of South Carolina) Context triple: [Nimarata Nikki Randhawa, officeEndTime (Governor of South Carolina), 2017-01-24]
-
A.
officeEndTime (Governor of North Carolina)
Indicates the time at which a Governor of North Carolina’s term in office concludes.
-
B.
officeEndForGovernorOfSouthCarolina
chosen
Indicates the date or point in time when an individual's term as Governor of South Carolina comes to an end.
-
C.
officeEndTime (Governor of Nebraska)
Indicates the time at which the Governor of Nebraska’s term in office concludes.
-
D.
officeEndTime (Governor of Maine)
Indicates the time at which the Governor of Maine’s term in office ends.
-
E.
officeEndTime (Lieutenant Governor of Pennsylvania)
Indicates the time at which the Lieutenant Governor of Pennsylvania’s term in office concludes.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.