Triple
T939600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frans Hals |
E20273
|
entity |
| Predicate | portraitSpecialization |
P21975
|
FINISHED |
| Object | civic guard group portraits |
—
|
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: civic guard group portraits | Statement: [Frans Hals, portraitSpecialization, civic guard group portraits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraitSpecialization Context triple: [Frans Hals, portraitSpecialization, civic guard group portraits]
-
A.
portraitArtist
Indicates that one entity is the artist who created a portrait depicting the other entity.
-
B.
photographer
Indicates that one entity takes photographs of another entity, typically in a professional or intentional capacity.
-
C.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
D.
isPhotographicSubject
Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
-
E.
specialFeature
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
- F. None of above. chosen
Provenance (4 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b38b7da08190ac0853655dab678a |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29c68f48190aecad10e351a99de |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b344f6f48190ba03ce593c94176b |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.