Triple
T8450472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvie’s Love |
E199785
|
entity |
| Predicate | maleLeadOccupation |
P21567
|
FINISHED |
| Object | jazz saxophonist |
—
|
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: jazz saxophonist | Statement: [Sylvie’s Love, maleLeadOccupation, jazz saxophonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maleLeadOccupation Context triple: [Sylvie’s Love, maleLeadOccupation, jazz saxophonist]
-
A.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
B.
hasLeadCharacterGender
Indicates that the primary or lead character in a work has a specified gender.
-
C.
majorActor
Indicates that the subject is a primary or leading participant in the action, event, or production involving the object.
-
D.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
E.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.