Triple
T28779897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Susan Vernon |
E726645
|
entity |
| Predicate | relatedWorkAdaptationOfCharacter |
P119717
|
FINISHED |
| Object | Love & Friendship (2016 film) |
—
|
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: Love & Friendship (2016 film) | Statement: [Lady Susan Vernon, relatedWorkAdaptationOfCharacter, Love & Friendship (2016 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedWorkAdaptationOfCharacter Context triple: [Lady Susan Vernon, relatedWorkAdaptationOfCharacter, Love & Friendship (2016 film)]
-
A.
adaptedWorkOfAuthor
Indicates that a work is an adaptation derived from, based on, or reinterpreting the original work of a specified author.
-
B.
collaboratedOnAdaptationOf
Indicates that two or more entities worked together on creating or producing an adaptation of an existing work.
-
C.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
D.
adaptationOfCharacterFrom
chosen
Indicates that one character is derived, modified, or reinterpreted from an existing character in another work or version.
-
E.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a00781b749c8190921c46e110cae0b0 |
completed | May 10, 2026, 12:20 p.m. |
| PD | Predicate disambiguation | batch_6a0077df3c8481909fabc9e84f5936e3 |
completed | May 10, 2026, 12:19 p.m. |
Created at: April 28, 2026, 6:19 a.m.