Triple
T1673755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Blind Girl |
E36182
|
entity |
| Predicate | hasReference |
P8581
|
FINISHED |
| Object | often discussed in Pre-Raphaelite scholarship |
—
|
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: often discussed in Pre-Raphaelite scholarship | Statement: [The Blind Girl, hasReference, often discussed in Pre-Raphaelite scholarship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReference Context triple: [The Blind Girl, hasReference, often discussed in Pre-Raphaelite scholarship]
-
A.
isReferencedIn
chosen
Indicates that one entity is cited, mentioned, or otherwise referred to within another entity.
-
B.
hasMapReference
Indicates that an entity is associated with a specific map or map location reference.
-
C.
hasCanonicalReference
Indicates that one entity serves as the authoritative or standard reference source for another entity.
-
D.
hasMainReferent
Indicates that one entity serves as the primary or central referent for another entity within a given context.
-
E.
hasColorReference
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.