Triple
T29504392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | alpha–beta pruning |
E748469
|
entity |
| Predicate | prunesWhen |
P14249
|
FINISHED |
| Object | alpha is greater than or equal to beta |
—
|
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: alpha is greater than or equal to beta | Statement: [alpha–beta pruning, prunesWhen, alpha is greater than or equal to beta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: prunesWhen Context triple: [alpha–beta pruning, prunesWhen, alpha is greater than or equal to beta]
-
A.
pruningType
Indicates the specific method or style of pruning applied to an entity (e.g., how it is cut back or trimmed).
-
B.
pruningTime
Indicates the time or period during which a pruning action is performed on something.
-
C.
pruningTolerance
Indicates how well an entity can withstand or recover from being cut back, trimmed, or pruned.
-
D.
vanishesWhen
chosen
Indicates that one entity ceases to exist, be visible, or be present whenever a specified condition involving another entity holds.
-
E.
isDeepCutOn
Indicates that one entity is a relatively obscure, less well-known, or non-mainstream example or item within the context of another entity.
- 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_69f0bd455a9c8190b40a3e8ea38cf61f |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66c35c9608190937a51b5de166390 |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f6633ac8a88190ab0cda62bbfcf9b0 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:26 p.m.