Triple
T23284708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One More Time |
E588954
|
entity |
| Predicate | hasRepetitiveHook |
P151703
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [One More Time, hasRepetitiveHook, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRepetitiveHook Context triple: [One More Time, hasRepetitiveHook, true]
-
A.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
-
B.
hasHook
Indicates that one entity possesses, is equipped with, or features a hook in relation to another entity or context.
-
C.
usesRepetition
Indicates that one entity employs repeated elements, actions, or patterns as a deliberate feature or technique in relation to another entity or context.
-
D.
hasRecurringElement
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
E.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
- 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_69e25d16e2c08190a291de254703129e |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1964600888190b40ecbefdc8aec64 |
completed | April 29, 2026, 5:25 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:59 p.m.