Triple

T1753798
Position Surface form Disambiguated ID Type / Status
Subject Richard Matheson E38505 entity
Predicate wrote P2831 FINISHED
Object Button, Button
"Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
 E197019 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: Button, Button | Statement: [Richard Matheson, wrote, Button, Button]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Button, Button
Context triple: [Richard Matheson, wrote, Button, Button]
  • A. BTN
    BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
  • B. Bar
    Bar is a coastal city and major seaport in southern Montenegro on the Adriatic Sea.
  • C. Bun
    Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
  • D. Berry
    Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
  • E. WIN button
    The WIN button was a widely distributed lapel pin used in the mid-1970s as part of U.S. President Gerald Ford’s “Whip Inflation Now” campaign to encourage public action against inflation.
  • 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: Button, Button
Triple: [Richard Matheson, wrote, Button, Button]
Generated description
"Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Button, Button
Target entity description: "Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
  • A. BTN
    BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
  • B. Bar
    Bar is a coastal city and major seaport in southern Montenegro on the Adriatic Sea.
  • C. Bun
    Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
  • D. Berry
    Berry is a historic province in central France known for its rural landscapes, medieval heritage, and traditional French culture.
  • E. WIN button
    The WIN button was a widely distributed lapel pin used in the mid-1970s as part of U.S. President Gerald Ford’s “Whip Inflation Now” campaign to encourage public action against inflation.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64169c508190a33074fb06e9c755 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e84c1c8190917edf14003cba81 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1a2fb9481909d9ed587921ca6b6 completed March 8, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69ada4e28830819082ed7facee14587f completed March 8, 2026, 4:33 p.m.
Created at: March 4, 2026, 7:31 p.m.