Triple

T6135057
Position Surface form Disambiguated ID Type / Status
Subject Battleground E136812 entity
Predicate starring P1507 FINISHED
Object George Murphy E164675 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: George Murphy | Statement: [Battleground, starring, George Murphy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Murphy
Context triple: [Battleground, starring, George Murphy]
  • A. George Murphy chosen
    George Murphy was an American song-and-dance man and film actor of the 1930s and 1940s who later became a U.S. senator from California.
  • B. 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.
  • C. Harry Davenport
    Harry Davenport was an American character actor best known for his numerous supporting roles in classic Hollywood films of the 1930s and 1940s.
  • D. William McMurray
    William McMurray was a historical figure after whom the Canadian city of Fort McMurray in Alberta was named, likely due to his role in the region’s early development or exploration.
  • E. Dan Duryea
    Dan Duryea was an American character actor best known for his distinctive portrayals of sneering villains and tough guys in film noir and classic Hollywood movies of the 1940s and 1950s.
  • 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_69c008a179388190a3b5a081bbf46d55 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c80a6088190a028967b682fed2b completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769d6f40c8190a59df50d44c50cea completed March 28, 2026, 5:40 a.m.
Created at: March 22, 2026, 4:15 p.m.