Triple

T2854260
Position Surface form Disambiguated ID Type / Status
Subject Edward Scissorhands E63162 entity
Predicate mainCharacter P1183 FINISHED
Object Peg Boggs
Peg Boggs is the kind-hearted Avon saleswoman who discovers and takes in Edward in the film "Edward Scissorhands," becoming his compassionate surrogate mother.
 E305271 NE FINISHED

How this triple was built (4 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: Peg Boggs | Statement: [Edward Scissorhands, mainCharacter, Peg Boggs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peg Boggs
Context triple: [Edward Scissorhands, mainCharacter, Peg Boggs]
  • A. Nannie
    Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
  • B. Celia Mae
    Celia Mae is the one-eyed, snake-haired receptionist at Monsters, Inc. and Mike Wazowski’s girlfriend in the Pixar animated film.
  • C. Marion Sparks
    Marion Sparks is a songwriter best known as the original composer of the blues standard "Every Day I Have the Blues."
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Peg Boggs
Triple: [Edward Scissorhands, mainCharacter, Peg Boggs]
Generated description
Peg Boggs is the kind-hearted Avon saleswoman who discovers and takes in Edward in the film "Edward Scissorhands," becoming his compassionate surrogate mother.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peg Boggs
Target entity description: Peg Boggs is the kind-hearted Avon saleswoman who discovers and takes in Edward in the film "Edward Scissorhands," becoming his compassionate surrogate mother.
  • A. Nannie
    Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
  • B. Celia Mae
    Celia Mae is the one-eyed, snake-haired receptionist at Monsters, Inc. and Mike Wazowski’s girlfriend in the Pixar animated film.
  • C. Marion Sparks
    Marion Sparks is a songwriter best known as the original composer of the blues standard "Every Day I Have the Blues."
  • D. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • F. None of above. chosen

Provenance (5 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf5f21348190a574fa86bc71c76f completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d8774cc8190aa6ed40b26c4a568 completed March 10, 2026, 1:32 p.m.
NEDg Description generation batch_69b01ea4e3a481909241383e2c4093d8 completed March 10, 2026, 1:37 p.m.
NED2 Entity disambiguation (via description) batch_69b01f1a9ac48190b8d2b5247cb2c3d8 completed March 10, 2026, 1:39 p.m.
Created at: March 6, 2026, 10:02 p.m.