Triple
T25877380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fur: An Imaginary Portrait of Diane Arbus (screenplay) |
E651941
|
entity |
| Predicate | isImaginaryPortrait |
P47899
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fur: An Imaginary Portrait of Diane Arbus (screenplay), isImaginaryPortrait, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isImaginaryPortrait Context triple: [Fur: An Imaginary Portrait of Diane Arbus (screenplay), isImaginaryPortrait, yes]
-
A.
isImaginary
chosen
Indicates that something exists only in the mind or imagination and does not have a corresponding real-world or physical existence.
-
B.
hasImaginaryCharacter
Indicates that an entity includes, features, or is associated with a fictional or imaginary character.
-
C.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
-
D.
isPurelyImaginary
Indicates that the entity exists only in imagination or theory and has no real or physical existence.
-
E.
isFaceOn
Indicates that one surface or side of an object is oriented directly toward, or aligned to face, another object or reference direction.
- 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_69e7ab3ad9d88190841ddcb93ab02e96 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f602e179ec8190aa45a4614673f7fc |
completed | May 2, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69f4939148dc81908706cec7d85291bc |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 8:13 a.m.