Triple
T22653824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queenie |
E559167
|
entity |
| Predicate | literaryCharacterBasisFor |
P43063
|
FINISHED |
| Object | Tulip in My Dog Tulip |
—
|
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: Tulip in My Dog Tulip | Statement: [Queenie, literaryCharacterBasisFor, Tulip in My Dog Tulip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryCharacterBasisFor Context triple: [Queenie, literaryCharacterBasisFor, Tulip in My Dog Tulip]
-
A.
fictionalCharacterAssociatedWith
Indicates that there is a notable connection or association between a fictional character and another entity, such as a work, creator, or universe.
-
B.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
C.
literarySeriesCharacter
Indicates that a character appears in, is part of, or is associated with a particular literary series.
-
D.
characterInBookBy
Indicates that a character appears in a book that was written by a specified author.
-
E.
fictionalCharacterFrom
chosen
Indicates that a fictional character originates from, or is created within, a particular work, universe, or source.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17659e4dc81909cf6943c1c986ef9 |
completed | April 29, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:06 p.m.