Triple
T24904556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josh Thomas |
E623667
|
entity |
| Predicate | characterInOwnWork |
P12208
|
FINISHED |
| Object | Nicholas (Everything's Gonna Be Okay) |
—
|
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: Nicholas (Everything's Gonna Be Okay) | Statement: [Josh Thomas, characterInOwnWork, Nicholas (Everything's Gonna Be Okay)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInOwnWork Context triple: [Josh Thomas, characterInOwnWork, Nicholas (Everything's Gonna Be Okay)]
-
A.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
B.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
C.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
D.
characterIn
chosen
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
worksWithFictionalCharacter
Indicates that one entity collaborates or interacts in a work-related context with another entity that is a fictional character.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5f6baf2d48190a6a4cd6501be87d2 |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 18, 2026, 5:27 a.m.