Triple

T7172442
Position Surface form Disambiguated ID Type / Status
Subject U.S. 1st Army E167231 entity
Predicate WWIICommander P47253 FINISHED
Object Courtney H. Hodges E346758 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: Courtney H. Hodges | Statement: [U.S. 1st Army, WWIICommander, Courtney H. Hodges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Courtney H. Hodges
Context triple: [U.S. 1st Army, WWIICommander, Courtney H. Hodges]
  • A. Courtney H. Hodges chosen
    Courtney H. Hodges was a senior U.S. Army general in World War II who commanded First Army in the European Theater, playing a key role in the liberation of Western Europe.
  • B. Terilyn A. Shropshire
    Terilyn A. Shropshire is an American film editor known for her work on numerous acclaimed films and television projects.
  • C. Cherelle L. Parker
    Cherelle L. Parker is an American politician who serves as the mayor of Philadelphia and is the first woman elected to the position in the city's history.
  • D. Kimberly J. Brown
    Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
  • E. Marta Heflin
    Marta Heflin was an American actress best known for her roles in several of Robert Altman’s ensemble films during the 1970s and 1980s.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e88b0a448190a19bd2d9e2a310a4 completed March 27, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbdab96c81909b9cfa10973fbf23 completed March 28, 2026, 12:38 p.m.
Created at: March 27, 2026, 2:48 p.m.