Triple
T31120659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Lynn |
E793212
|
entity |
| Predicate | relationshipTypeWithBoJack |
P10690
|
FINISHED |
| Object | former co-star |
—
|
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: former co-star | Statement: [Sarah Lynn, relationshipTypeWithBoJack, former co-star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithBoJack Context triple: [Sarah Lynn, relationshipTypeWithBoJack, former co-star]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
C.
relationshipToJack
Indicates the specific type of personal or social connection an entity has with Jack.
-
D.
relationshipCharacterizedAs
Indicates that one relationship is described, defined, or typified in terms of another specified characteristic or relational type.
-
E.
showsRelationshipWith
Indicates that one entity visually or explicitly presents or demonstrates its connection or association with 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 9:04 p.m.