Triple

T36749383
Position Surface form Disambiguated ID Type / Status
Subject Pat and Margaret E907861 entity
Predicate starredJulieWaltersAs P186544 FINISHED
Object Margaret
Margaret is the title character played by Julie Walters in the British television film "Pat and Margaret."
 E2198782 NE FINISHED

How this triple was built (3 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: Margaret | Statement: [Pat and Margaret, starredJulieWaltersAs, Margaret]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Margaret
Triple: [Pat and Margaret, starredJulieWaltersAs, Margaret]
Generated description
Margaret is the title character played by Julie Walters in the British television film "Pat and Margaret."
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: starredJulieWaltersAs
Context triple: [Pat and Margaret, starredJulieWaltersAs, Margaret]
  • A. starredActorWith
    Indicates that one entity participated as an actor in a production together with another specified actor.
  • B. starredActor
    Indicates that an actor performed a leading or significant role in a particular production or work.
  • C. starredAustralianActress
    Indicates that a person performed a starring role as an actress in an Australian production.
  • D. supportingActorAwardRecipient
    Indicates that an entity has received an award specifically for a supporting acting role in a performance or production.
  • E. leadActress
    Indicates that the subject is the primary female performer in the specified film, show, or production.
  • F. None of above. chosen

Provenance (7 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_69f76e76d10881909ec1679bc043108c completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fe1a1ca4819084c196f0041f0be2 completed May 5, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3d1791ab708190a5b46dfd03da1e13 completed June 25, 2026, 11:57 a.m.
NEDg Description generation batch_6a3d1ba7e34881909cd0a2c7471566b9 completed June 25, 2026, 12:14 p.m.
NED2 Entity disambiguation (via description) batch_6a3d5f8f6e708190bf7dc9444f080ac3 completed June 25, 2026, 5:04 p.m.
PD Predicate disambiguation batch_69f7cf7890008190a8bc355ff2d61c86 completed May 3, 2026, 10:43 p.m.
PDg Predicate description generation batch_69f9fd66eed48190bdc26a8def328c2d completed May 5, 2026, 2:23 p.m.
Created at: May 3, 2026, 4:12 p.m.