Triple

T1132906
Position Surface form Disambiguated ID Type / Status
Subject Christopher Hartley E23071 entity
Predicate familyName P18 FINISHED
Object Hartley
Hartley is an English-language surname of Old English origin, commonly associated with various notable figures across fields such as science, politics, and the arts.
 E131240 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: Hartley | Statement: [Christopher Hartley, familyName, Hartley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hartley
Context triple: [Christopher Hartley, familyName, Hartley]
  • A. Hartley
    Hartley is a small census-designated community located in Solano County, California.
  • B. Sholto
    Sholto is a masculine given name of Scottish origin, historically associated with figures such as military leaders and nobles.
  • C. Hannington
    Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic character.
  • D. Thirlby
    Thirlby is the surname of Olivia Thirlby, an American actress known for roles in films such as "Juno" and "Dredd."
  • E. Morley
    Morley is a town in West Yorkshire, England, situated between Leeds and Bradford within the Leeds City Council metropolitan area.
  • 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: Hartley
Triple: [Christopher Hartley, familyName, Hartley]
Generated description
Hartley is an English-language surname of Old English origin, commonly associated with various notable figures across fields such as science, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hartley
Target entity description: Hartley is an English-language surname of Old English origin, commonly associated with various notable figures across fields such as science, politics, and the arts.
  • A. Hartley
    Hartley is a small census-designated community located in Solano County, California.
  • B. Sholto
    Sholto is a masculine given name of Scottish origin, historically associated with figures such as military leaders and nobles.
  • C. Hannington
    Hannington is a small rural village in Wiltshire, England, known for its traditional English countryside setting and historic character.
  • D. Thirlby
    Thirlby is the surname of Olivia Thirlby, an American actress known for roles in films such as "Juno" and "Dredd."
  • E. Morley
    Morley is a town in West Yorkshire, England, situated between Leeds and Bradford within the Leeds City Council metropolitan area.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bbfcdf848190a2917d796ca84b74 completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5ead716c81908bf7c6531cbff7f1 completed March 7, 2026, 5:21 p.m.
NEDg Description generation batch_69ac5f2f566c8190a5630cee9c77e231 completed March 7, 2026, 5:23 p.m.
NED2 Entity disambiguation (via description) batch_69ac5fc6b6748190837a640623411eea completed March 7, 2026, 5:26 p.m.
Created at: March 1, 2026, 7:44 p.m.