Triple
T25517987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Carolina Democratic primary |
E639560
|
entity |
| Predicate | winner2004 |
P122073
|
FINISHED |
| Object | John Edwards |
—
|
NE NERFINISHED |
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: John Edwards | Statement: [South Carolina Democratic primary, winner2004, John Edwards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winner2004 Context triple: [South Carolina Democratic primary, winner2004, John Edwards]
-
A.
resultIn2002Election
Indicates the outcome or consequence that occurred specifically in relation to the 2002 election.
-
B.
has2020Winner
Indicates that a given competition, award, or event is associated with the entity that won it in the year 2020.
-
C.
electionWinner
chosen
Indicates that the subject is the candidate who received the highest support and officially won a particular election.
-
D.
winnerParty
Indicates the political party that has won a particular election, contest, or decision-making process.
-
E.
ranPresidentialCandidate
Indicates that the subject has been a candidate in a presidential election.
- 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_69e75dbe32e48190a62d749a0ff2a96a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 2:57 p.m.