Triple
T23546770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N.O.R.E. (CD edition) |
E577916
|
entity |
| Predicate | notablePosseCut |
P152747
|
FINISHED |
| Object | Banned from T.V. |
—
|
NE NERFINISHED |
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: Banned from T.V. | Statement: [N.O.R.E. (CD edition), notablePosseCut, Banned from T.V.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePosseCut Context triple: [N.O.R.E. (CD edition), notablePosseCut, Banned from T.V.]
-
A.
roughCutOf
Indicates that one media item is an early, unpolished or preliminary edited version of another media item.
-
B.
commonCut
Indicates that two or more entities share at least one identical segment or portion that has been cut or divided in the same way.
-
C.
notableTrim
Indicates that an entity has a particularly significant or distinguished trim level or decorative variant compared to standard versions.
-
D.
cutter
Indicates that an entity is used to cut or divide another entity.
-
E.
isCutInto
Indicates that one entity is divided or separated into pieces or segments that become the other entity.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aecb567c8190a54d2c3b63282af5 |
completed | April 29, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:11 p.m.