Triple

T3898708
Position Surface form Disambiguated ID Type / Status
Subject Come and Get It E90433 entity
Predicate awardReceivedBy P11 FINISHED
Object Walter Brennan E91109 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: Walter Brennan | Statement: [Come and Get It, awardReceivedBy, Walter Brennan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Brennan
Context triple: [Come and Get It, awardReceivedBy, Walter Brennan]
  • A. Walter Brennan chosen
    Walter Brennan was an American character actor renowned for his prolific film career and for winning a record three Academy Awards for Best Supporting Actor.
  • B. Garth Algar
    Garth Algar is a shy, nerdy, and endearingly awkward best friend and co-host to Wayne Campbell in the comedy franchise "Wayne's World."
  • C. Lew Ayres
    Lew Ayres was an American actor best known for his starring role in the anti-war film "All Quiet on the Western Front" and for his long-running portrayal of Dr. Kildare.
  • D. Kurtwood Smith
    Kurtwood Smith is an American character actor best known for playing the strict father Red Forman on the sitcom "That '70s Show" and for roles in films like "RoboCop."
  • E. Jack Palance
    Jack Palance was an American actor known for his intense, rugged screen presence and memorable roles in films such as "Shane" and "City Slickers."
  • 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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecefa3608190a7a20ed6df6a64b2 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5285093208190a2ba00afcbd8a261 completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:21 p.m.