Triple

T4284806
Position Surface form Disambiguated ID Type / Status
Subject Solihull E97241 entity
Predicate hasSuburb P747 FINISHED
Object Shirley
Shirley is a suburban area within the town of Solihull in the West Midlands, England, known for its residential neighborhoods and local shopping facilities.
 E426866 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: Shirley | Statement: [Solihull, hasSuburb, Shirley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shirley
Context triple: [Solihull, hasSuburb, Shirley]
  • A. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • B. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • C. Shirley
    Shirley is an English surname of Old English origin that has also become a common given name.
  • D. Shirley
    Shirley is a suburban area in the London Borough of Croydon, known for its residential neighborhoods and proximity to green spaces and nearby districts like West Wickham.
  • E. Shirley
    "Shirley" is a social and political novel by Charlotte Brontë set during the industrial unrest of early 19th-century England, exploring themes of class conflict, gender roles, and economic hardship.
  • 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: Shirley
Triple: [Solihull, hasSuburb, Shirley]
Generated description
Shirley is a suburban area within the town of Solihull in the West Midlands, England, known for its residential neighborhoods and local shopping facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shirley
Target entity description: Shirley is a suburban area within the town of Solihull in the West Midlands, England, known for its residential neighborhoods and local shopping facilities.
  • A. Shirley
    Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
  • B. Shirley
    Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
  • C. Shirley
    Shirley is an English surname of Old English origin that has also become a common given name.
  • D. Shirley
    "Shirley" is a social and political novel by Charlotte Brontë set during the industrial unrest of early 19th-century England, exploring themes of class conflict, gender roles, and economic hardship.
  • E. Shirley
    Shirley is a suburban area in the London Borough of Croydon, known for its residential neighborhoods and proximity to green spaces and nearby districts like West Wickham.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3505bff588190919a4ef547f607c2 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7c2023c8190a2359f8cabcecd2c completed March 14, 2026, 7:32 p.m.
NEDg Description generation batch_69b5b94471588190a27e7df972f072b1 completed March 14, 2026, 7:38 p.m.
NED2 Entity disambiguation (via description) batch_69b5ba4262b481908378f7ebdc9a7c9c completed March 14, 2026, 7:42 p.m.
Created at: March 12, 2026, 11:07 p.m.