Triple
T3865941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille Benson |
E91851
|
entity |
| Predicate | portrayedRoleType |
P16411
|
FINISHED |
| Object | motherly characters |
—
|
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: motherly characters | Statement: [Lucille Benson, portrayedRoleType, motherly characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedRoleType Context triple: [Lucille Benson, portrayedRoleType, motherly characters]
-
A.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
B.
actingRoleType
chosen
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
C.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
D.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
E.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3b8d988190b56d42ac1521e19c |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.