Triple
T22930979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA World Cup bronze medal |
E569437
|
entity |
| Predicate | firstPlaceContrast |
P150298
|
FINISHED |
| Object | FIBA World Cup gold medal |
—
|
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: FIBA World Cup gold medal | Statement: [FIBA World Cup bronze medal, firstPlaceContrast, FIBA World Cup gold medal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPlaceContrast Context triple: [FIBA World Cup bronze medal, firstPlaceContrast, FIBA World Cup gold medal]
-
A.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
B.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
-
C.
standardContrastedWith
Indicates a relationship where one standard is explicitly compared or set in opposition to another standard to highlight their differences.
-
D.
dramaticContrastWith
Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
-
E.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
- 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18131956c8190b8c850fc1d57a119 |
completed | April 29, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:44 p.m.