Triple

T255903
Position Surface form Disambiguated ID Type / Status
Subject Gordon E. Moore E5436 entity
Predicate familyName P18 FINISHED
Object Moore
Moore is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
 E32614 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: Moore | Statement: [Gordon E. Moore, familyName, Moore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Moore
Context triple: [Gordon E. Moore, familyName, Moore]
  • A. Moore
    Moore is the middle name of Edward M. Kennedy, the long-serving U.S. senator from Massachusetts and prominent member of the Kennedy political family.
  • B. Miller
    Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
  • C. McClintock
    McClintock is a surname most notably associated with Barbara McClintock, the pioneering American cytogeneticist and Nobel Prize laureate recognized for her discovery of genetic transposition.
  • D. Richardson
    Richardson is a suburban city in the Dallas–Fort Worth metropolitan area known for its telecommunications industry and the University of Texas at Dallas.
  • E. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • 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: Moore
Triple: [Gordon E. Moore, familyName, Moore]
Generated description
Moore is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Moore
Target entity description: Moore is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
  • A. Moore
    Moore is the middle name of Edward M. Kennedy, the long-serving U.S. senator from Massachusetts and prominent member of the Kennedy political family.
  • B. Miller
    Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
  • C. McClintock
    McClintock is a surname most notably associated with Barbara McClintock, the pioneering American cytogeneticist and Nobel Prize laureate recognized for her discovery of genetic transposition.
  • D. Richardson
    Richardson is a suburban city in the Dallas–Fort Worth metropolitan area known for its telecommunications industry and the University of Texas at Dallas.
  • E. Milhous
    Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5669008190978bbd7308be11f7 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3766038008190aa896920bbf9d713 completed Feb. 28, 2026, 11:12 p.m.
NEDg Description generation batch_69a376baec9c8190b2d0e3c198a4b106 completed Feb. 28, 2026, 11:14 p.m.
NED2 Entity disambiguation (via description) batch_69a3770a1c2c8190975320ede10717b2 completed Feb. 28, 2026, 11:15 p.m.
Created at: Feb. 28, 2026, 2:55 a.m.