Triple

T2382636
Position Surface form Disambiguated ID Type / Status
Subject Gouverneur Morris E46344 entity
Predicate familyName P18 FINISHED
Object Morris
Morris is a common English-language surname borne by numerous notable figures in politics, arts, sports, and other fields.
 E260758 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: Morris | Statement: [Gouverneur Morris, familyName, Morris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Morris
Context triple: [Gouverneur Morris, familyName, Morris]
  • A. Morris
    Morris is the given first name of Moe Berg, the American Major League Baseball catcher who later became a World War II intelligence officer.
  • B. Swinton
    Swinton is a town in the City of Salford, Greater Manchester, England, known historically for its role in the coal mining and textile industries.
  • C. The Dinky
    The Dinky is a short commuter rail shuttle service that connects Princeton University to the nearby Princeton Junction station on New Jersey Transit's Northeast Corridor line.
  • D. Norris
    Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
  • E. Mott
    Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
  • 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: Morris
Triple: [Gouverneur Morris, familyName, Morris]
Generated description
Morris is a common English-language surname borne by numerous notable figures in politics, arts, sports, and other fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Morris
Target entity description: Morris is a common English-language surname borne by numerous notable figures in politics, arts, sports, and other fields.
  • A. Morris
    Morris is the given first name of Moe Berg, the American Major League Baseball catcher who later became a World War II intelligence officer.
  • B. Swinton
    Swinton is a town in the City of Salford, Greater Manchester, England, known historically for its role in the coal mining and textile industries.
  • C. The Dinky
    The Dinky is a short commuter rail shuttle service that connects Princeton University to the nearby Princeton Junction station on New Jersey Transit's Northeast Corridor line.
  • D. Norris
    Norris is a surname most notably associated with influential American politician George W. Norris, a progressive-era U.S. senator from Nebraska.
  • E. Mott
    Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
  • 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc7bafa248190a68e8f1e081f4817 completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8b790bc8190ba399e252acec750 completed March 9, 2026, 11:02 a.m.
NEDg Description generation batch_69aeabb22c708190898b44cdd8b97ff6 completed March 9, 2026, 11:14 a.m.
NED2 Entity disambiguation (via description) batch_69aeac141ca88190a9a91d0f5b25c341 completed March 9, 2026, 11:16 a.m.
Created at: March 4, 2026, 7:57 p.m.