Triple
T10260283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turn Your Love Around |
E240576
|
entity |
| Predicate | hasCrossoverHitStatus |
P56239
|
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: [Turn Your Love Around, hasCrossoverHitStatus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossoverHitStatus Context triple: [Turn Your Love Around, hasCrossoverHitStatus, true]
-
A.
hasCrossoverHits
Indicates that an entity (such as an artist or work) has achieved significant success across multiple distinct genres, markets, or audience categories.
-
B.
hasCrossovers
Indicates that one entity features or participates in crossover appearances or interactions with another entity or set of entities.
-
C.
crossesOverWith
Indicates that one entity intersects or overlaps with another, typically by passing across or through its path, boundary, or extent.
-
D.
hasCross
Indicates that one entity possesses, displays, or is marked by a cross in relation to another entity or context.
-
E.
crossoverHit
chosen
Indicates that a creative work has achieved significant popularity or success across multiple distinct audience segments, genres, or markets beyond its original target.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:32 a.m.