Triple

T16148106
Position Surface form Disambiguated ID Type / Status
Subject Why Women Kill E391838 entity
Predicate stars P1956 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: [Why Women Kill, stars, Allison Tolman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allison Tolman
Context triple: [Why Women Kill, stars, 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. Kathryn Railly
    Kathryn Railly is a psychiatrist who becomes a key ally and companion to time traveler James Cole in the science fiction film "12 Monkeys."
  • E. 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."
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d9551e081908391061b092ff31b completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a9ebf08190aa21cdff051f4ba2 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.