Triple
T33172355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donna Hayward |
E849067
|
entity |
| Predicate | portrayedByInTVSeries |
P1507
|
FINISHED |
| Object | Lara Flynn Boyle |
—
|
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: Lara Flynn Boyle | Statement: [Donna Hayward, portrayedByInTVSeries, Lara Flynn Boyle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByInTVSeries Context triple: [Donna Hayward, portrayedByInTVSeries, Lara Flynn Boyle]
-
A.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
playedInTVSeries
Indicates that an entity (typically a person or character) performed or appeared as part of the cast in a particular television series.
-
C.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
D.
laterPortrayedAs
Indicates that an entity is subsequently depicted or represented as another character, role, or form in a later work or context.
-
E.
portrayedByAlsoKnownFor
Indicates that an entity is portrayed by a person who is also notably known for another specific role or 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_69f3495be8808190bbf427733df08aad |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: May 1, 2026, 1:29 a.m.