Triple
T23550658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Of the Girl |
E578031
|
entity |
| Predicate | isDeepCut |
P124131
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Of the Girl, isDeepCut, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDeepCut Context triple: [Of the Girl, isDeepCut, true]
-
A.
isDeepCutOn
chosen
Indicates that one entity is a relatively obscure, less well-known, or non-mainstream example or item within the context of another entity.
-
B.
includesDeepCuts
Indicates that the subject contains lesser-known, rare, or non-mainstream items from the object’s collection or repertoire.
-
C.
isCutInto
Indicates that one entity is divided or separated into pieces or segments that become the other entity.
-
D.
isDeepest
Indicates that one entity has the greatest depth relative to a specified reference or set of comparable entities.
-
E.
hasCut
Indicates that one entity has made or possesses a cut in, on, or through 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aece662081909022e7a29f966ca3 |
completed | April 29, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:11 p.m.