Triple
T8171267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Félix Faure |
E190824
|
entity |
| Predicate | prePoliticalCareer |
P29120
|
FINISHED |
| Object | leather merchant |
—
|
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: leather merchant | Statement: [Félix Faure, prePoliticalCareer, leather merchant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prePoliticalCareer Context triple: [Félix Faure, prePoliticalCareer, leather merchant]
-
A.
politicalPrecursorOf
Indicates that one political entity, movement, or event served as a significant antecedent or foundation that influenced or led to the development of another.
-
B.
startTimeOfPoliticalCareer
Indicates the point in time when an individual’s political career officially began.
-
C.
hasPoliticalPositionOn
Indicates that an entity holds or expresses a specific stance, view, or opinion regarding a political issue, policy, or topic.
-
D.
professionOfCandidate
chosen
Indicates that one entity is the profession or occupational role held by the candidate entity.
-
E.
incumbentBeforeElection
Indicates that the subject was already holding the relevant office or position prior to the specified 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb48056d0c819094575090a41e0083 |
completed | March 31, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:39 p.m.