Triple
T12441978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Adolphe Thiers |
E297295
|
entity |
| Predicate | depictsNotableFor |
P22
|
FINISHED |
| Object | role in French politics |
—
|
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: role in French politics | Statement: [Portrait of Adolphe Thiers, depictsNotableFor, role in French politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsNotableFor Context triple: [Portrait of Adolphe Thiers, depictsNotableFor, role in French politics]
-
A.
depictsNotablePerson
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
-
B.
notableFor
chosen
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
C.
notableFeatureOn
Indicates that one entity is a prominent or distinguishing feature located on or part of another entity.
-
D.
notableDepictionBy
Indicates that an entity is significantly portrayed or represented by a particular creator, work, or medium.
-
E.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.