Triple
T13747905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breathless |
E330264
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | The Wedding Song |
E1060400
|
NE 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: The Wedding Song | Statement: [Breathless, hasTrack, The Wedding Song]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Wedding Song Context triple: [Breathless, hasTrack, The Wedding Song]
-
A.
The Wedding Song
chosen
"The Wedding Song" is a track by the band Silhouette, likely featuring their characteristic melodic rock or progressive sound.
-
B.
Wedding Song
"Wedding Song" is a heartfelt folk ballad by Bob Dylan, widely interpreted as a personal tribute to his then-wife Sara Dylan.
-
C.
A Wedding
"A Wedding" is a 1978 ensemble comedy film directed by Robert Altman that satirically portrays the chaos and social dynamics surrounding an upper-class wedding.
-
D.
The Wedding
"The Wedding" is a romantic drama film featuring Cynda Williams in a prominent role, exploring themes of love, family, and commitment.
-
E.
The Wedding
"The Wedding" is a Caroline-era stage comedy by English dramatist James Shirley, known for its witty exploration of courtship, marriage, and social manners.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02132a108190aca728b95e83af01 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06d9fd48190a10b86a0d68fac70 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:08 p.m.