Triple
T32256089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilles Caron |
E824025
|
entity |
| Predicate | notablePhotoSubject |
P9792
|
FINISHED |
| Object | student protests in Paris |
—
|
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: student protests in Paris | Statement: [Gilles Caron, notablePhotoSubject, student protests in Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePhotoSubject Context triple: [Gilles Caron, notablePhotoSubject, student protests in Paris]
-
A.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
B.
photographerOfNotableImage
Indicates that a person is the photographer who captured a specific notable or widely recognized image.
-
C.
isPhotographicSubject
chosen
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
D.
subjectOfMainPanorama
Indicates that an entity is the primary focus or central object depicted in a main panoramic view or image.
-
E.
notablePortraitSubject
Indicates that the subject is a person who is prominently or famously depicted in a portrait created by the other entity.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:41 a.m.