Triple
T2068104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Avenol |
E45950
|
entity |
| Predicate | termStartAsSecretaryGeneral |
P1056
|
FINISHED |
| Object | 1933 |
—
|
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: 1933 | Statement: [Joseph Avenol, termStartAsSecretaryGeneral, 1933]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termStartAsSecretaryGeneral Context triple: [Joseph Avenol, termStartAsSecretaryGeneral, 1933]
-
A.
secretaryGeneralStart
chosen
Indicates the date or point in time when an individual begins serving as secretary general of an organization or body.
-
B.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
C.
termStartAsVicePresident
Indicates that an entity begins its term in office holding the position of vice president.
-
D.
firstSecretaryGeneral
Indicates that the subject is the first person to hold the position of secretary general of the specified organization or body.
-
E.
termStartAsActingGovernor
Indicates that a person’s term in office began while they were serving in the capacity of an acting governor rather than as a fully appointed or elected governor.
- 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_69a8891b38288190abd572ccad9b6928 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9f362f48190b1b0e560424c3aef |
completed | March 7, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69abb7aee9b48190999620176e3a6ee2 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.