Triple
T30925830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Girl (The Office U.S.) |
E787850
|
entity |
| Predicate | featuresDocumentaryCrewDevice |
P35865
|
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: [Hot Girl (The Office U.S.), featuresDocumentaryCrewDevice, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDocumentaryCrewDevice Context triple: [Hot Girl (The Office U.S.), featuresDocumentaryCrewDevice, yes]
-
A.
featureCrew
Indicates that a particular crew member is highlighted or designated as a featured participant within a crew-related context.
-
B.
featuresCast
Indicates that a creative work includes a particular person or group as part of its cast.
-
C.
hasCrewFeature
Indicates that a crew possesses or is characterized by a particular feature, attribute, or capability.
-
D.
featuresDevice
chosen
Indicates that one entity includes, incorporates, or provides the other entity as a device within it or as part of its functionality.
-
E.
filmAbility
Indicates that one entity has the capability or skill to create, direct, or otherwise produce films involving 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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00474f08908190bc8ae3b320ec887b |
completed | May 10, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_6a0045dc3bd48190a9e0520f3ef3f067 |
completed | May 10, 2026, 8:46 a.m. |
Created at: April 29, 2026, 8:51 p.m.