Triple
T34779033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Symphony |
E1002589
|
entity |
| Predicate | hasFictionalOboist |
P62476
|
FINISHED |
| Object | Hailey Rutledge |
—
|
NE NERFINISHED |
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: Hailey Rutledge | Statement: [New York Symphony, hasFictionalOboist, Hailey Rutledge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalOboist Context triple: [New York Symphony, hasFictionalOboist, Hailey Rutledge]
-
A.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
B.
hasFictionalSpeaker
Indicates that a work, text, or expression is presented as being spoken by an invented or non-real speaker rather than an actual person.
-
C.
hasFictionalPerformer
chosen
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
D.
isFictionalBearer
Indicates that an entity serves as the (typically named) holder or possessor of something within a fictional or imaginary context.
-
E.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
Created at: May 3, 2026, 3:59 p.m.