Triple
T28616383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CreateSemaphore |
E724281
|
entity |
| Predicate | minimumInitialCount |
P26954
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [CreateSemaphore, minimumInitialCount, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumInitialCount Context triple: [CreateSemaphore, minimumInitialCount, 0]
-
A.
minimumSize
Indicates that there is a lower bound or smallest allowable value for the size of something in the relationship.
-
B.
minimumNumberOfMembers
Indicates the smallest allowable or required number of members that must be present or involved in a given context or group.
-
C.
minimumGrant
Indicates that there is a lowest allowable or required amount of a grant associated with an entity or agreement.
-
D.
numberOfInitials
Indicates the count of initial letters (such as initials in a name) associated with an entity.
-
E.
minimumNumber
chosen
Indicates that the associated value is the smallest or least quantity allowed, required, or observed within a given set or context.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 4:32 a.m.