Triple
T6851191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Great Debate |
E158018
|
entity |
| Predicate | audienceRole |
P72617
|
FINISHED |
| Object | reacts with laughter and applause |
—
|
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: reacts with laughter and applause | Statement: [The Great Debate, audienceRole, reacts with laughter and applause]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audienceRole Context triple: [The Great Debate, audienceRole, reacts with laughter and applause]
-
A.
speakerRole
Indicates the functional role or capacity in which an entity is acting as a speaker within a communicative event.
-
B.
roleInVox
Indicates that an entity holds a specific role or function within a Vox-related context, such as a project, system, or organization named or described as "Vox."
-
C.
theaterRole
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
-
D.
audienceSetting
Indicates the context or environment in which an audience is situated or addressed.
-
E.
roleInScene
Indicates that an entity participates in a particular scene with a specific role or function within that scene.
- 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_69c6882fae988190864cbba788c5ebb4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d84e6fb08190915954be5b0df2d8 |
completed | March 27, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1668a7c8190ae93951f9ba2df10 |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:20 p.m.