Triple

T13364134
Position Surface form Disambiguated ID Type / Status
Subject Kim Boggs E318893 entity
Predicate hasMother P1909 FINISHED
Object Peg Boggs E305271 NE 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: Peg Boggs | Statement: [Kim Boggs, hasMother, Peg Boggs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peg Boggs
Context triple: [Kim Boggs, hasMother, Peg Boggs]
  • A. Peg Boggs chosen
    Peg Boggs is the kind-hearted Avon saleswoman who discovers and takes in Edward in the film "Edward Scissorhands," becoming his compassionate surrogate mother.
  • B. Gertrude Hobbs
    Gertrude Hobbs was the wife of Scottish evangelist and devotional writer Oswald Chambers, who preserved and published many of his teachings after his death.
  • C. Cissie Colpitts
    Cissie Colpitts is a central character in Peter Greenaway’s darkly comic film "Drowning by Numbers," known for her involvement in a generational tale of murder, games, and ritualized counting.
  • D. Tott Doneeta
    Tott Doneeta is a Twi'lek Jedi Knight from the Star Wars Expanded Universe, known for his loyalty and role in the ancient Jedi conflicts depicted in the Tales of the Jedi comics.
  • E. Janie Page
    Janie Page is a fictional character who is the daughter of Neal Page in the film "Planes, Trains and Automobiles."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69da628c71ac81908cfa36342077766e completed April 11, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7267e9d608190b36f58a92d4a9964 completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:32 p.m.