Triple
T35527638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Show |
E1026712
|
entity |
| Predicate | turnedFaceAndHeelMultipleTimes |
P183206
|
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: [The Big Show, turnedFaceAndHeelMultipleTimes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnedFaceAndHeelMultipleTimes Context triple: [The Big Show, turnedFaceAndHeelMultipleTimes, true]
-
A.
turnedFace
Indicates that one entity directed or rotated its face toward another entity or specific direction.
-
B.
turnedHeel
Indicates that an entity abruptly reversed direction or changed course, often implying a sudden shift in stance or behavior.
-
C.
turnAgainst
Indicates a shift in allegiance where one entity begins to oppose, betray, or act hostile toward another it previously supported or was aligned with.
-
D.
turns
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
E.
defacedWith
Indicates that one entity has been damaged, marred, or vandalized using another entity as the means or material of defacement.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79a53ccc481908421ae16e69aa8a4 |
completed | May 3, 2026, 6:56 p.m. |
Created at: May 3, 2026, 4:04 p.m.