Triple
T35471192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikki Heat book series |
E1025211
|
entity |
| Predicate | realWorldAuthor |
P107441
|
FINISHED |
| Object | unknown (house name) |
—
|
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: unknown (house name) | Statement: [Nikki Heat book series, realWorldAuthor, unknown (house name)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realWorldAuthor Context triple: [Nikki Heat book series, realWorldAuthor, unknown (house name)]
-
A.
realWorldPerformer
Indicates that an entity serves as the actual, real-world performer of an action, role, or content represented in another entity.
-
B.
realWorldName
Indicates that an entity’s name in a real-world context is given or associated with another value.
-
C.
authorRealNameOfCreator
Indicates that a person’s real, legal, or birth name is the true identity behind a creator who may be known by a pseudonym or handle.
-
D.
hasAuthorRealName
chosen
Indicates that an entity (such as a work or pseudonym) is associated with the actual, legal name of its author.
-
E.
canonicalAuthor
Indicates that an entity is the officially recognized or standard author of a given work or resource.
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.