Triple
T20993626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nina Blount |
E517087
|
entity |
| Predicate | characterInWorkBasedOn |
P2004
|
FINISHED |
| Object | novel Vile Bodies |
—
|
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: novel Vile Bodies | Statement: [Nina Blount, characterInWorkBasedOn, novel Vile Bodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInWorkBasedOn Context triple: [Nina Blount, characterInWorkBasedOn, novel Vile Bodies]
-
A.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
B.
characterBasedOn
chosen
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
C.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
D.
inspiredByFictionalCharacter
Indicates that an entity’s characteristics, actions, or creation are influenced or modeled after a specific fictional character.
-
E.
basedOnCharacterBy
Indicates that one work, adaptation, or portrayal is derived from or inspired by a character created by another entity.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1d829081908de889c542734393 |
completed | April 21, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e5dbec80708190a49bccab7ff97e7b |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 1:50 p.m.