Triple
T34779043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Symphony |
E1002589
|
entity |
| Predicate | hasFictionalPercussionist |
P62476
|
FINISHED |
| Object | Dee Dee |
—
|
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: Dee Dee | Statement: [New York Symphony, hasFictionalPercussionist, Dee Dee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPercussionist Context triple: [New York Symphony, hasFictionalPercussionist, Dee Dee]
-
A.
hasFictionalPerformer
chosen
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
B.
hasPowerfulPercussion
Indicates that an entity features or produces percussion that is notably strong, intense, or forceful in impact.
-
C.
hasDrummer
Indicates that one entity serves as the drummer for, or plays drums in, another entity such as a band or musical group.
-
D.
hasFictionalSong
Indicates that one entity includes, features, or is associated with a song that is fictional or exists only within a narrative context.
-
E.
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.
- 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_69ff9a25407c81909faa86e72a7a9d17 |
completed | May 9, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69ff99c613688190a03b2f93d5ccad2b |
completed | May 9, 2026, 8:32 p.m. |
Created at: May 3, 2026, 3:59 p.m.