Triple
T23978635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Lockhart |
E604443
|
entity |
| Predicate | spinOffMainCharacterOf |
P138903
|
FINISHED |
| Object | The Good Fight |
—
|
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: The Good Fight | Statement: [Diane Lockhart, spinOffMainCharacterOf, The Good Fight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spinOffMainCharacterOf Context triple: [Diane Lockhart, spinOffMainCharacterOf, The Good Fight]
-
A.
spinOffCharacter
Indicates that one character originates as a derivative or secondary creation from another, typically branching off into its own distinct narrative or work.
-
B.
spinOffSeriesProtagonist
chosen
Indicates that a character serves as the main protagonist of a spin-off series derived from an original work.
-
C.
spinOffRole
Indicates that one role or position has been derived or created as a secondary or offshoot role from another original role.
-
D.
laterMainCharacterOf
Indicates that one entity becomes the main character of a work at a later point in time, succeeding another main character.
-
E.
spinoffAppearance
Indicates that an entity appears in a derivative or spinoff work related to another original work or series.
- 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_69e29543f40c819087700b7a272afb60 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d2bba58c8190a1a4b5bcc5bc9d98 |
completed | April 29, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:26 p.m.