Triple

T21039821
Position Surface form Disambiguated ID Type / Status
Subject Angela Lansbury as Eleanor Iselin E518290 entity
Predicate politicalRoleInFiction P101621 FINISHED
Object behind-the-scenesPowerBroker 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: behind-the-scenesPowerBroker | Statement: [Angela Lansbury as Eleanor Iselin, politicalRoleInFiction, behind-the-scenesPowerBroker]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: politicalRoleInFiction
Context triple: [Angela Lansbury as Eleanor Iselin, politicalRoleInFiction, behind-the-scenesPowerBroker]
  • A. politicalRoleInPlot chosen
    Indicates that an entity holds a specific political function, position, or influence within the context of a particular plot or storyline.
  • B. fictionalUniverseRole
    Indicates the role or function an entity has within a particular fictional universe or narrative setting.
  • C. politicalPartyInFiction
    Indicates that a political party appears or operates within a fictional work or fictional universe.
  • D. fictionalCharacter
    Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
  • E. literaryRole
    Indicates the specific narrative or functional role an entity holds within a literary work or text.
  • 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_69e0b50438e08190917e2538bb8bc034 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fceed9148190903adb3b55f65242 completed April 21, 2026, 4:28 a.m.
PD Predicate disambiguation batch_69e5dbf6728881908a2a43a5c8804a2a completed April 20, 2026, 7:55 a.m.
Created at: April 16, 2026, 2:14 p.m.