Triple
T1374498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Thomas |
E30188
|
entity |
| Predicate | numberOfTimesCandidateForPresidentOfTheUnitedStates |
P21021
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Norman Thomas, numberOfTimesCandidateForPresidentOfTheUnitedStates, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTimesCandidateForPresidentOfTheUnitedStates Context triple: [Norman Thomas, numberOfTimesCandidateForPresidentOfTheUnitedStates, 6]
-
A.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
B.
wonPresidentialElection
Indicates that one entity achieved victory over others in a presidential election.
-
C.
reElectedToPresidency
Indicates that an individual, having previously served as president, is chosen again to hold the office of the presidency.
-
D.
ranPresidentialCandidate
chosen
Indicates that the subject has been a candidate in a presidential election.
-
E.
hasIncumbentPresidentCandidate
Indicates that a political entity (such as a party, election, or race) has a current office-holding president running as a candidate in that contest.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2f7aeb08190b52ef1058c18327e |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.