Triple

T13384349
Position Surface form Disambiguated ID Type / Status
Subject Good Girls E319400 entity
Predicate castMember P1668 FINISHED
Object Allison Tolman E142382 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: Allison Tolman | Statement: [Good Girls, castMember, Allison Tolman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allison Tolman
Context triple: [Good Girls, castMember, Allison Tolman]
  • A. Allison Tolman chosen
    Allison Tolman is an American actress best known for her breakout role as Deputy Molly Solverson in the television series "Fargo."
  • B. Melissa Hudson
    Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
  • C. Kirsten Nelson
    Kirsten Nelson is an American actress best known for her role as police chief Karen Vick on the television series "Psych."
  • D. Alice Patten
    Alice Patten is a British actress best known internationally for her role as an English documentary filmmaker in the acclaimed Indian film "Rang De Basanti."
  • E. Bridget Hedison
    Bridget Hedison is an American artist and photographer known for her contemporary mixed-media works and for being married to actress Jodie Foster.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce80158819082156eaeaeda3bd8 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7268cf04c8190a35fd48ce81c149e completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:33 p.m.