Triple
T14407333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronda Rousey vs Becky Lynch vs Charlotte Flair |
E357232
|
entity |
| Predicate | mainEventNumber |
P46841
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Ronda Rousey vs Becky Lynch vs Charlotte Flair, mainEventNumber, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainEventNumber Context triple: [Ronda Rousey vs Becky Lynch vs Charlotte Flair, mainEventNumber, 1]
-
A.
mainEventFor
Indicates that one event is the primary or central event associated with another entity, such as a context, grouping, or larger occurrence.
-
B.
numberOfMainEvents
chosen
Indicates the total count of primary or most significant events associated with a given entity or context.
-
C.
mainEvents
Indicates that the referenced entities are the primary or most significant events within a given context, sequence, or narrative.
-
D.
mainEventStipulation
Indicates that a specified condition, requirement, or rule must be satisfied for the main event or primary occurrence in a given context.
-
E.
previousNumberOfEvents
Indicates the count of events that occurred before a specified point or reference event.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90c7a068819081b4b516983a1412 |
completed | April 14, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69de2aa1b57881909a033eac8545c417 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:17 a.m.