Triple
T4269790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Take |
E96912
|
entity |
| Predicate | editingScope |
P25607
|
FINISHED |
| Object | local face regions |
—
|
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: local face regions | Statement: [Best Take, editingScope, local face regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: editingScope Context triple: [Best Take, editingScope, local face regions]
-
A.
encodingScope
Indicates the range or extent of content or information that is covered, represented, or captured by a particular encoding.
-
B.
reviewScope
Indicates the extent, boundaries, or aspects of something that are covered, considered, or evaluated during a review.
-
C.
editorStart
Indicates the point in time or position at which an editor begins working on, modifying, or reviewing a content item or resource.
-
D.
writingSystemScope
Indicates the range or extent of content, languages, or contexts to which a particular writing system applies or is used.
-
E.
scopeType
chosen
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
- 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ffa30c08190913622ffec47d33d |
completed | March 12, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.