Triple
T6542489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberto Durán |
E168323
|
entity |
| Predicate | numberOfWeightDivisionsWithWorldTitles |
P72287
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Roberto Durán, numberOfWeightDivisionsWithWorldTitles, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWeightDivisionsWithWorldTitles Context triple: [Roberto Durán, numberOfWeightDivisionsWithWorldTitles, 4]
-
A.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
B.
numberOfMrOlympiaTitles
Indicates the number of Mr. Olympia bodybuilding titles that an individual has won.
-
C.
hasWorldChampionship
Indicates that an entity possesses, has won, or holds a world championship title or status.
-
D.
numberOfTitleDefenses
Indicates the number of times an entity has successfully defended a previously won title or championship.
-
E.
WorldChampionshipMedalsTotal
Indicates the total number of medals an entity has won at world championship competitions.
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6ce0538f48190abf3160681901c17 |
completed | March 27, 2026, 6:35 p.m. |
Created at: March 27, 2026, 1:50 p.m.