Triple
T35985319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extreme Rules |
E1040692
|
entity |
| Predicate | matchTypeOftenFeatured |
P48257
|
FINISHED |
| Object | steel cage match |
—
|
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: steel cage match | Statement: [Extreme Rules, matchTypeOftenFeatured, steel cage match]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchTypeOftenFeatured Context triple: [Extreme Rules, matchTypeOftenFeatured, steel cage match]
-
A.
featuredMatchType
chosen
Indicates the specific category or kind of match that is highlighted or given special prominence.
-
B.
featuresMatchType
Indicates that the features involved conform to, or are compatible with, a specified type or classification.
-
C.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
D.
hasFeatured
Indicates that one entity has prominently included, highlighted, or showcased another entity in a special or notable way.
-
E.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
- 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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:07 p.m.