Triple

T14626766
Position Surface form Disambiguated ID Type / Status
Subject Cliff DeYoung E343368 entity
Predicate notableWork P4 FINISHED
Object Glory
"Glory" is a 1989 American war drama film about one of the first African-American regiments in the Union Army during the Civil War, acclaimed for its powerful performances and historical significance.
 E178789 NE FINISHED

How this triple was built (4 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: Glory | Statement: [Cliff DeYoung, notableWork, Glory]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Glory
Context triple: [Cliff DeYoung, notableWork, Glory]
  • A. Glory
    Glory is the airline callsign used by UNI Air, a Taiwanese regional carrier.
  • B. Glory
    Glory is a feminine given name most notably associated with American professional basketball player Glory Johnson.
  • C. Glory
    "Glory" is a song performed by American singer Celia.
  • D. Glory
    "Glory" is a hip-hop track by American rapper Hodgy Beats that showcases his introspective lyrics and distinctive alternative rap style.
  • E. Glory
    "Glory" is an Academy Award–winning civil rights anthem by John Legend and Common, written for the 2014 film *Selma* and celebrated for its powerful commentary on racial justice.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Glory
Triple: [Cliff DeYoung, notableWork, Glory]
Generated description
"Glory" is a 1989 American war drama film about one of the first African-American regiments in the Union Army during the Civil War, acclaimed for its powerful performances and historical significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Glory
Target entity description: "Glory" is a 1989 American war drama film about one of the first African-American regiments in the Union Army during the Civil War, acclaimed for its powerful performances and historical significance.
  • A. Glory chosen
    "Glory" is a 1989 American war drama film about the first African-American regiment in the Union Army during the U.S. Civil War, acclaimed for its powerful performances and historical significance.
  • B. Glory
    "Glory" is an Academy Award–winning civil rights anthem by John Legend and Common, written for the 2014 film *Selma* and celebrated for its powerful commentary on racial justice.
  • C. Glory
    "Glory" is a hip-hop track by American rapper Hodgy Beats that showcases his introspective lyrics and distinctive alternative rap style.
  • D. Glory
    "Glory" is a song by the American rock band Pippin, recognized as one of their notable tracks.
  • E. Glory
    "Glory" is a song performed by American singer Celia.
  • F. None of above.

Provenance (5 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb46a4a9081908472b0a542028a7f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda92c25ac8190ba931c009e7ace19 completed May 8, 2026, 9:13 a.m.
NEDg Description generation batch_69fdb7e5aa6481908d4933e3932c5d03 completed May 8, 2026, 10:16 a.m.
NED2 Entity disambiguation (via description) batch_69fdb841f3a88190867c635950a1492c completed May 8, 2026, 10:17 a.m.
Created at: April 10, 2026, 1:26 a.m.