Triple
T18216453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monon Bell Classic |
E436171
|
entity |
| Predicate | trophyWeight |
P130285
|
FINISHED |
| Object | approximately 300 pounds |
—
|
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: approximately 300 pounds | Statement: [Monon Bell Classic, trophyWeight, approximately 300 pounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trophyWeight Context triple: [Monon Bell Classic, trophyWeight, approximately 300 pounds]
-
A.
trophyHeight
Indicates the height measurement associated with a trophy.
-
B.
trophy
Indicates that one entity is a trophy awarded or possessed in relation to another entity, typically as a result of winning or achieving something.
-
C.
trophyColor
Indicates the color attribute assigned to a trophy in the relationship.
-
D.
trophySignificance
Indicates that one entity (typically a trophy) holds a particular level or type of importance, value, or meaning in relation to another entity.
-
E.
trophyCount
Indicates the number of trophies associated with a given entity.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e47765a081908d0bbca1245f89ba |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.