Triple
T35806658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chokeslam |
E1035117
|
entity |
| Predicate | commonCounter |
P198348
|
FINISHED |
| Object | arm drag reversal |
—
|
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: arm drag reversal | Statement: [Chokeslam, commonCounter, arm drag reversal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonCounter Context triple: [Chokeslam, commonCounter, arm drag reversal]
-
A.
usesCounters
Indicates that one entity employs or relies on counters (such as tallying or tracking mechanisms) in relation to another entity or process.
-
B.
count
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
C.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
D.
commonOn
Indicates that two or more entities share the same location, context, or medium where they are present or occur together.
-
E.
commonness
Indicates how frequently or typically something occurs or is found relative to other things.
- 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fedec693b08190b0f8bfdb921e0766 |
completed | May 9, 2026, 7:14 a.m. |
| PD | Predicate disambiguation | batch_69fede16c1d48190a20d8a9c5722c307 |
completed | May 9, 2026, 7:11 a.m. |
| PDg | Predicate description generation | batch_69fedec5e1708190a0b13be7533d55d8 |
completed | May 9, 2026, 7:14 a.m. |
Created at: May 3, 2026, 4:06 p.m.