Triple
T1958469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | You Light Up My Life (Whitney Houston song) |
E42325
|
entity |
| Predicate | recordingArtistGender |
P25113
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [You Light Up My Life (Whitney Houston song), recordingArtistGender, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordingArtistGender Context triple: [You Light Up My Life (Whitney Houston song), recordingArtistGender, female]
-
A.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
B.
creatorSexOrGender
chosen
Indicates that the specified sex or gender is the sex or gender of the creator of the referenced work or entity.
-
C.
producerArtist
Indicates that one entity serves as the producer (e.g., overseeing or managing the creation) of a work created or performed by the artist entity.
-
D.
hasAuthorGender
Indicates that an entity (such as a work or publication) is associated with an author of a specified gender.
-
E.
hasFemaleVocalist
Indicates that the subject entity features or includes at least one female vocalist as a performer.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.