Triple

T13085414
Position Surface form Disambiguated ID Type / Status
Subject Ella Rumpf E310317 entity
Predicate notableWork P4 FINISHED
Object War
"War" is a film featuring Swiss actress Ella Rumpf in a prominent role.
E1021106 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: War | Statement: [Ella Rumpf, notableWork, War]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: War
Context triple: [Ella Rumpf, notableWork, War]
  • A. War
    War is a small town in McDowell County, West Virginia, known as one of the southernmost communities in the state and for its history as a coal mining town.
  • B. War
    "War" is a musical track from the film score of James Cameron's 2009 science fiction epic "Avatar," composed by James Horner.
  • C. War
    "War" is a nonfiction book by Sebastian Junger that chronicles the experiences of American soldiers in Afghanistan’s Korengal Valley, exploring the psychology, brotherhood, and brutality of modern combat.
  • D. War
    War is an American funk and soul band best known for their 1970s hits blending rock, jazz, Latin, and R&B influences, including songs like "Low Rider" and "Why Can't We Be Friends?".
  • E. War
    "War" is a politically charged reggae song by Bob Marley & The Wailers, best known for its lyrics adapted from a speech by Ethiopian Emperor Haile Selassie I calling for global peace and equality.
  • 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: War
Triple: [Ella Rumpf, notableWork, War]
Generated description
"War" is a film featuring Swiss actress Ella Rumpf in a prominent role.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: War
Target entity description: "War" is a film featuring Swiss actress Ella Rumpf in a prominent role.
  • A. War
    "War" is a musical track from the film score of James Cameron's 2009 science fiction epic "Avatar," composed by James Horner.
  • B. War
    "War" is a nonfiction book by Sebastian Junger that chronicles the experiences of American soldiers in Afghanistan’s Korengal Valley, exploring the psychology, brotherhood, and brutality of modern combat.
  • C. War
    War is one of the Four Horsemen of the Apocalypse in Neil Gaiman and Terry Pratchett’s "Good Omens," depicted as a glamorous, red-haired war correspondent who personifies and incites human conflict.
  • D. War
    "War" is a 1970 protest soul song by Edwin Starr, famous for its powerful anti-war message and the iconic refrain "War, what is it good for? Absolutely nothing!"
  • E. War
    War is U2’s politically charged 1983 rock album known for its anthemic songs and focus on themes of conflict and social justice.
  • F. None of above. chosen

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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981361e8c819099376435aa3a7aa3 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d61060188190911eb3e135dc25ac completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6dae595908190b27980e48514cda5 completed May 3, 2026, 5:19 a.m.
NED2 Entity disambiguation (via description) batch_69f6db8f68a4819091d8e67d9c8eec81 completed May 3, 2026, 5:22 a.m.
Created at: April 9, 2026, 9:02 p.m.