Triple
T32258673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BEST theorem |
E824089
|
entity |
| Predicate | givesCountAs |
P173896
|
FINISHED |
| Object | T_r × ∏_v (outdeg(v) − 1)! for a root r |
—
|
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: T_r × ∏_v (outdeg(v) − 1)! for a root r | Statement: [BEST theorem, givesCountAs, T_r × ∏_v (outdeg(v) − 1)! for a root r]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givesCountAs Context triple: [BEST theorem, givesCountAs, T_r × ∏_v (outdeg(v) − 1)! for a root r]
-
A.
areCountedBy
Indicates that one entity serves as the counting mechanism, record, or process by which the quantity of another entity is determined.
-
B.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
C.
count
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
D.
isCountedAs
Indicates that one entity is treated or included as part of the tally, total, or quantitative assessment of another entity.
-
E.
gulCount
Indicates the number of goals (gul) scored or attributed in a given context.
- 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_69f3490db0748190bfef6e50c95d39d3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc5652e08190b519631b7d497e75 |
completed | May 3, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:41 a.m.