Triple

T28103348
Position Surface form Disambiguated ID Type / Status
Subject Lumberjack Tavern E710294 entity
Predicate hasVictimInCase P170970 FINISHED
Object Maurice Chenoweth
Maurice Chenoweth was the victim in the notorious 1986 murder case at the Lumberjack Tavern in Michigan’s Upper Peninsula, which inspired the novel and film "Anatomy of a Murder."
 E1803516 NE FINISHED

How this triple was built (3 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: Maurice Chenoweth | Statement: [Lumberjack Tavern, hasVictimInCase, Maurice Chenoweth]
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: Maurice Chenoweth
Triple: [Lumberjack Tavern, hasVictimInCase, Maurice Chenoweth]
Generated description
Maurice Chenoweth was the victim in the notorious 1986 murder case at the Lumberjack Tavern in Michigan’s Upper Peninsula, which inspired the novel and film "Anatomy of a Murder."
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasVictimInCase
Context triple: [Lumberjack Tavern, hasVictimInCase, Maurice Chenoweth]
  • A. hasVictimCount
    Indicates the number of victims associated with a particular event, action, or entity.
  • B. isVictimOf
    Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
  • C. hasMainVictim
    Indicates that an event, action, or harmful situation primarily targets or affects a specific victim as its main subject.
  • D. hasVictimRoleWith chosen
    Indicates a relationship in which one entity occupies or is assigned the role of victim in relation to another entity or event.
  • E. hasVictimsCount
    Indicates the number of victims associated with a particular event, action, or entity.
  • F. None of above.

Provenance (6 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_69ef9b71fdb081908b4a61cd7ff147c1 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f6db1f3ec48190a82e7d893d3c76ba completed May 3, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a15c928a18481908b5f05b23bab2514 completed May 26, 2026, 4:24 p.m.
NEDg Description generation batch_6a15ca4a3d548190ac7be49c7d35ee0b completed May 26, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15cbc2fa6c8190a3d8a4b60ab6104c completed May 26, 2026, 4:35 p.m.
PD Predicate disambiguation batch_69f6d82adfa481908a5e196d2e18c73f completed May 3, 2026, 5:07 a.m.
Created at: April 27, 2026, 9:06 p.m.