Triple

T161682
Position Surface form Disambiguated ID Type / Status
Subject James Shirley E3300 entity
Predicate familyName P18 FINISHED
Object Shirley
Shirley is an English surname of Old English origin that has also become a common given name.
 E20376 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: [James Shirley, familyName, Shirley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shirley
Context triple: [James Shirley, familyName, 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. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • D. Harriet
    Harriet is the given name of Harriet Beecher Stowe, the 19th-century American author best known for writing the anti-slavery novel "Uncle Tom's Cabin."
  • E. Their Eyes Were Watching God
    Their Eyes Were Watching God is a seminal 1937 novel by Zora Neale Hurston that follows the life and self-discovery of Janie Crawford in the early 20th-century American South.
  • 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: [James Shirley, familyName, Shirley]
Generated description
Shirley is an English surname of Old English origin that has also become a common given name.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shirley
Target entity description: Shirley is an English surname of Old English origin that has also become a common given name.
  • 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. Sula
    Sula is a 1973 novel by American author Toni Morrison that explores Black female friendship, community, and identity in a small Ohio town.
  • D. Harriet
    Harriet is the given name of Harriet Beecher Stowe, the 19th-century American author best known for writing the anti-slavery novel "Uncle Tom's Cabin."
  • E. Their Eyes Were Watching God
    Their Eyes Were Watching God is a seminal 1937 novel by Zora Neale Hurston that follows the life and self-discovery of Janie Crawford in the early 20th-century American South.
  • 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_69a2527757ec819090b8becb2cf1a862 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a2585877648190a2ec320182a69343 completed Feb. 28, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2db53aaf081909577b743e3660e5c completed Feb. 28, 2026, 12:10 p.m.
NEDg Description generation batch_69a2dbc0d1a881908d47bb4ebe2e3a26 completed Feb. 28, 2026, 12:12 p.m.
NED2 Entity disambiguation (via description) batch_69a2dc307978819091019dff30f84e57 completed Feb. 28, 2026, 12:14 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.