Triple
T33244819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cervenka |
E851066
|
entity |
| Predicate | bearerInfluence |
P63153
|
FINISHED |
| Object | influence on American punk music |
—
|
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: influence on American punk music | Statement: [Cervenka, bearerInfluence, influence on American punk music]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerInfluence Context triple: [Cervenka, bearerInfluence, influence on American punk music]
-
A.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
B.
incorporatesInfluence
Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
-
C.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
D.
hasSignificantInfluenceIn
chosen
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
E.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
- 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_69f34962386c81909ddc3bf9e18ddeb8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: May 1, 2026, 1:31 a.m.