Triple

T7453573
Position Surface form Disambiguated ID Type / Status
Subject Michael Spence E172064 entity
Predicate familyName P18 FINISHED
Object Spence
Spence is a surname most notably associated with Michael Spence, the Nobel Prize–winning economist known for his work on signaling in markets.
 E665961 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: Spence | Statement: [Michael Spence, familyName, Spence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Spence
Context triple: [Michael Spence, familyName, Spence]
  • A. Spence
    Spence is an Australian federal electoral division in South Australia, represented in the House of Representatives.
  • B. Spence
    Spence is a residential suburb in the Belconnen district of Canberra, in the Australian Capital Territory.
  • C. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • D. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • E. Spencer
    Spencer is a 2021 biographical psychological drama film depicting Princess Diana during a tense Christmas holiday with the British royal family, starring Kristen Stewart in the lead role.
  • 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: Spence
Triple: [Michael Spence, familyName, Spence]
Generated description
Spence is a surname most notably associated with Michael Spence, the Nobel Prize–winning economist known for his work on signaling in markets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Spence
Target entity description: Spence is a surname most notably associated with Michael Spence, the Nobel Prize–winning economist known for his work on signaling in markets.
  • A. Spence
    Spence is an Australian federal electoral division in South Australia, represented in the House of Representatives.
  • B. Spence
    Spence is a residential suburb in the Belconnen district of Canberra, in the Australian Capital Territory.
  • C. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • D. Spencer
    Spencer is a small city located in Oklahoma County, Oklahoma, within the Oklahoma City metropolitan area.
  • E. Spencer
    Spencer is a small town in central Massachusetts known for its New England character and historic mill village roots.
  • 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_69c68a66554c8190add75c65942c0317 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f3ac5c2081908ab03f8bd4586f94 completed March 27, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c834597d94819081f57de7d5ae30af completed March 28, 2026, 8:04 p.m.
NEDg Description generation batch_69c834c4a6b0819091cd9ecd1581cfe4 completed March 28, 2026, 8:06 p.m.
NED2 Entity disambiguation (via description) batch_69c83560fa908190a8c1d8862f9a31f9 completed March 28, 2026, 8:09 p.m.
Created at: March 27, 2026, 3:14 p.m.