Triple
T33683290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonah Levin |
E862958
|
entity |
| Predicate | hasFictionalTalent |
P199543
|
FINISHED |
| Object | songwriting |
—
|
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: songwriting | Statement: [Jonah Levin, hasFictionalTalent, songwriting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalTalent Context triple: [Jonah Levin, hasFictionalTalent, songwriting]
-
A.
hasFictionalSpecialization
Indicates that an entity’s area of focus, expertise, or role is within a fictional or imaginative domain rather than a real-world specialization.
-
B.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
C.
hasFictionalGenreCharacteristic
Indicates that something possesses a specific characteristic or attribute related to a fictional genre.
-
D.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
E.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
- F. None of above. chosen
Provenance (4 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_69f3498662b48190904442c39df84fb7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
| PDg | Predicate description generation | batch_69ff4163a8548190b0eaafd0a377b141 |
completed | May 9, 2026, 2:14 p.m. |
Created at: May 1, 2026, 1:43 a.m.