Triple
T29002649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Red-Haired Girl |
E736344
|
entity |
| Predicate | nameInSomeAdaptations |
P130420
|
FINISHED |
| Object | Heather |
—
|
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: Heather | Statement: [Little Red-Haired Girl, nameInSomeAdaptations, Heather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameInSomeAdaptations Context triple: [Little Red-Haired Girl, nameInSomeAdaptations, Heather]
-
A.
laterAdaptationName
Indicates that the object is the name of a later adaptation derived from or based on the subject.
-
B.
hasProtagonistNameInFilmAdaptation
chosen
Indicates that a specific name is used for the story’s main character in a particular film adaptation.
-
C.
inLaterAdaptations
Indicates that something appears, occurs, or is introduced only in subsequent or later adaptations of an original work or source.
-
D.
adaptationOfCharacterFrom
Indicates that one character is derived, modified, or reinterpreted from an existing character in another work or version.
-
E.
adaptationAppearances
Indicates the relationship between an original work and the specific appearances or instances of its adaptations in other media or versions.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fbd59d0819095a6bfb40c7c96d5 |
completed | May 2, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 9:35 a.m.