Triple
T32644477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umaga |
E834562
|
entity |
| Predicate | numberOfIntercontinentalTitleReigns |
P113847
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Umaga, numberOfIntercontinentalTitleReigns, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIntercontinentalTitleReigns Context triple: [Umaga, numberOfIntercontinentalTitleReigns, 2]
-
A.
IntercontinentalChampionshipReigns
chosen
Indicates the number or record of times an entity has held the Intercontinental Championship title.
-
B.
intercontinentalChampion
Indicates that an entity holds or has held the title of intercontinental champion in a competitive context.
-
C.
championshipReignsCount
Indicates the number of times an entity has held a particular championship title.
-
D.
intercontinentalTitle
Indicates a title or championship that is contested between or spans multiple continents.
-
E.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a01ca0db6f08190bed479584114e63d |
completed | May 11, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_6a01c96ff4a08190a4fbf0cebbda95b4 |
completed | May 11, 2026, 12:20 p.m. |
Created at: May 1, 2026, 1:07 a.m.