Triple
T10007757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gonna Get Over You |
E198294
|
entity |
| Predicate | hasRetroInfluence |
P91531
|
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: [Gonna Get Over You, hasRetroInfluence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetroInfluence Context triple: [Gonna Get Over You, hasRetroInfluence, true]
-
A.
wereInfluencedBy
Indicates that one entity’s ideas, actions, or characteristics were shaped or affected by another entity.
-
B.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
C.
hasEnduringInfluenceOn
Indicates that one entity exerts a lasting, long-term impact on another entity’s state, development, or behavior.
-
D.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
E.
hasUrbanInfluence
Indicates that one entity exerts or reflects the characteristics, impact, or style of an urban area on another entity.
- 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_69ca830fcca48190bbbd9b20c233835f |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd187fe481908556ea896c528ea4 |
completed | April 2, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69cd3584b2b4819096ff2625a7f5f1b5 |
completed | April 1, 2026, 3:11 p.m. |
Created at: March 30, 2026, 8:52 p.m.