Triple
T3136921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki Haley |
E65553
|
entity |
| Predicate | officeHeldOf |
P45587
|
FINISHED |
| Object | Governor of South Carolina |
—
|
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: Governor of South Carolina | Statement: [Nikki Haley, officeHeldOf, Governor of South Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldOf Context triple: [Nikki Haley, officeHeldOf, Governor of South Carolina]
-
A.
officeHeldDuring
Indicates that a person occupied a specific official position during a particular time period.
-
B.
officeHeldUnder
Indicates that one entity holds or has held an official position, role, or office under the authority, jurisdiction, or administration of another entity.
-
C.
officeHeldIn
Indicates that a particular office or position is held within or associated with a specific geographic or administrative location.
-
D.
officeHeldByMember
Indicates that a specific office or position is held or occupied by a particular member.
-
E.
officeHeldInPeriod
Indicates that an entity held a particular office or position during a specified time period.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada564eacc8190a54d07b4eb31c196 |
completed | March 8, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:05 p.m.