Triple

T15437767
Position Surface form Disambiguated ID Type / Status
Subject Terrence Ross E369811 entity
Predicate familyName P18 FINISHED
Object Ross
Ross is a common surname of Scottish and English origin borne by numerous notable individuals across sports, entertainment, politics, and other fields.
E87043 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: Ross | Statement: [Terrence Ross, familyName, Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ross
Context triple: [Terrence Ross, familyName, Ross]
  • A. John
    John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
  • B. John
    John Seigenthaler was an American journalist, editor, and civil rights advocate best known for his long tenure at The Tennessean and his work promoting First Amendment rights.
  • C. John
    John B. Magruder was a Confederate major general during the American Civil War, known for his leadership in the Peninsula Campaign and his flamboyant personality.
  • D. John
    John Bacon was a 19th-century American politician who served in the Wisconsin State Assembly.
  • E. John
    John is the given name of John Francis Bentley, the English architect best known for designing Westminster Cathedral in London.
  • 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: Ross
Triple: [Terrence Ross, familyName, Ross]
Generated description
Ross is a common surname of Scottish and English origin borne by numerous notable individuals across sports, entertainment, politics, and other fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ross
Target entity description: Ross is a common surname of Scottish and English origin borne by numerous notable individuals across sports, entertainment, politics, and other fields.
  • A. Ross chosen
    Ross is a common Scottish-origin surname borne by numerous notable figures across fields such as politics, science, arts, and sports.
  • B. Ross
    Ross is a small, affluent residential town in Marin County, California, known for its wooded setting and quiet, upscale character.
  • C. Ross
    Ross is a historic region in the Scottish Highlands traditionally associated with Clan Ross and known for its rugged landscapes and coastal scenery.
  • D. John
    John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
  • E. John
    John Seigenthaler was an American journalist, editor, and civil rights advocate best known for his long tenure at The Tennessean and his work promoting First Amendment rights.
  • F. None of above.

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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edca064819081510bf303271062 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a7d44481909a26b5cc331a3259 completed May 9, 2026, 11:59 a.m.
NEDg Description generation batch_69ff23348a448190a2a2953a18b29aaf completed May 9, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff240af68c8190af88834d97a42afb completed May 9, 2026, 12:09 p.m.
Created at: April 10, 2026, 3:21 a.m.