Triple
T30595879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Please Don’t Stop Loving Me |
E778786
|
entity |
| Predicate | hasPerformerRelationship |
P26739
|
FINISHED |
| Object | duo |
—
|
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: duo | Statement: [Please Don’t Stop Loving Me, hasPerformerRelationship, duo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerformerRelationship Context triple: [Please Don’t Stop Loving Me, hasPerformerRelationship, duo]
-
A.
associatedWithPerformer
Indicates a relationship in which something (such as a work, event, or role) is connected or linked to a specific performer.
-
B.
performerRelationshipContext
chosen
Indicates the contextual nature or circumstances of the relationship between a performer and another entity (such as an event, work, or role).
-
C.
hasPerformerFamily
Indicates that an entity has a family member who performs or participates as a performer in relation to that entity.
-
D.
hasPerformerLabelAssociation
Indicates a relationship linking a performer to an associated label, such as a record label or organizational affiliation.
-
E.
associatedPerformerPersona
Indicates a relationship where a performer is linked to a specific persona or role identity they adopt in their performances.
- 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_69f224a1570c8190a85d3ac330479a79 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 29, 2026, 8:24 p.m.