Triple
T27736069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ThreadStart |
E697530
|
entity |
| Predicate | commonUsagePattern |
P12995
|
FINISHED |
| Object | new Thread(SomeMethod).Start() |
—
|
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: new Thread(SomeMethod).Start() | Statement: [ThreadStart, commonUsagePattern, new Thread(SomeMethod).Start()]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonUsagePattern Context triple: [ThreadStart, commonUsagePattern, new Thread(SomeMethod).Start()]
-
A.
usagePattern
chosen
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
B.
frequentUseCase
Indicates a situation, scenario, or pattern of use that occurs regularly or more often than others in relation to the subject.
-
C.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
D.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
E.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7817daf00819098936402e75ab0a6 |
completed | May 3, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
Created at: April 27, 2026, 3:12 p.m.