Triple
T33567292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France in art |
E859792
|
entity |
| Predicate | hasKeyPersonification |
P81304
|
FINISHED |
| Object | Marianne |
—
|
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: Marianne | Statement: [France in art, hasKeyPersonification, Marianne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyPersonification Context triple: [France in art, hasKeyPersonification, Marianne]
-
A.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
-
B.
isPersonificationOf
chosen
Indicates that one entity represents or embodies an abstract concept, quality, or non-human thing in human form.
-
C.
hasMainPersonality
Indicates that one entity possesses or is characterized by a primary or dominant personality associated with another entity.
-
D.
hasPerson
Indicates that an entity is associated with or includes a specific person.
-
E.
hasKeyThinker
Indicates that an entity is associated with or characterized by a particular key thinker (e.g., philosopher, theorist, or intellectual figure) central to its ideas or development.
- 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_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1:40 a.m.