Triple

T7007770
Position Surface form Disambiguated ID Type / Status
Subject Henry Daniell E162500 entity
Predicate familyName P18 FINISHED
Object Daniell
Daniell is an English-language surname borne by various notable individuals in fields such as acting, science, and public service.
 E635788 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: Daniell | Statement: [Henry Daniell, familyName, Daniell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daniell
Context triple: [Henry Daniell, familyName, Daniell]
  • A. Daniels
    Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
  • B. Heinsohn
    Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
  • C. Dwan
    Dwan is the female lead character in the 1976 remake of King Kong, portrayed as the shipwrecked aspiring actress who forms a unique bond with the giant ape.
  • D. Dinneen
    Dinneen is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
  • E. Tibbett
    Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
  • 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: Daniell
Triple: [Henry Daniell, familyName, Daniell]
Generated description
Daniell is an English-language surname borne by various notable individuals in fields such as acting, science, and public service.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daniell
Target entity description: Daniell is an English-language surname borne by various notable individuals in fields such as acting, science, and public service.
  • A. Daniels
    Daniels is a common English-language surname borne by numerous notable individuals across politics, sports, entertainment, and other fields.
  • B. Heinsohn
    Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
  • C. Dwan
    Dwan is the female lead character in the 1976 remake of King Kong, portrayed as the shipwrecked aspiring actress who forms a unique bond with the giant ape.
  • D. Dinneen
    Dinneen is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
  • E. Tibbett
    Tibbett is a surname of English origin borne by various notable individuals in fields such as music, sports, and the arts.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc36e3fc8190957445132a9ffb5f completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a43c3a081909b9150d36ba107f5 completed March 28, 2026, 5:42 a.m.
NEDg Description generation batch_69c76b3c87708190a04c48c41bb9904b completed March 28, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69c76bb8c7788190bf54b805f651e28e completed March 28, 2026, 5:48 a.m.
Created at: March 27, 2026, 2:33 p.m.