Triple
T30176472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Songs |
E767071
|
entity |
| Predicate | featuresArtistOccupation |
P24742
|
FINISHED |
| Object | actress |
—
|
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: actress | Statement: [Love Songs, featuresArtistOccupation, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresArtistOccupation Context triple: [Love Songs, featuresArtistOccupation, actress]
-
A.
artistOccupation
chosen
Indicates the professional role or job that an artist holds or performs.
-
B.
hasMusicalArtistOccupation
Indicates that an entity has an occupation or professional role as a musical artist.
-
C.
featuresArtistAs
Indicates that one entity includes or presents another entity in the role of an artist (e.g., a work, event, or product featuring a specific artist).
-
D.
featuresArtistAsRecordingArtist
Indicates that an item (such as a recording or release) includes a particular artist in the role of the recording artist.
-
E.
featuresArtistFromRegion
Indicates that something includes or highlights an artist whose origin or affiliation is with a specified geographic region.
- 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_69f2247ba20c81909d34f2bfed706e1e |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
Created at: April 29, 2026, 7:25 p.m.