Triple

T10552017
Position Surface form Disambiguated ID Type / Status
Subject Hazel Brooks E248974 entity
Predicate givenName P17 FINISHED
Object Hazel
Hazel is a feminine given name of English origin, derived from the hazel tree and often associated with nature and greenish-brown eye color.
 E873679 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: Hazel | Statement: [Hazel Brooks, givenName, Hazel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hazel
Context triple: [Hazel Brooks, givenName, Hazel]
  • A. Hazel
    Hazel is a simple, good-hearted drifter in John Steinbeck’s novel "Cannery Row," known for his loyalty, comic misunderstandings, and unexpected moments of insight.
  • B. Hazel
    "Hazel" is a song featured on Bob Dylan’s 1974 album Planet Waves.
  • C. Hazel
    Hazel is a classic American television sitcom from the 1960s centered on a witty live-in maid and the suburban family she works for.
  • D. Hazel
    Hazel is the given first name of American Baseball Hall of Famer Kiki Cuyler.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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: Hazel
Triple: [Hazel Brooks, givenName, Hazel]
Generated description
Hazel is a feminine given name of English origin, derived from the hazel tree and often associated with nature and greenish-brown eye color.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hazel
Target entity description: Hazel is a feminine given name of English origin, derived from the hazel tree and often associated with nature and greenish-brown eye color.
  • A. Hazel
    Hazel is a simple, good-hearted drifter in John Steinbeck’s novel "Cannery Row," known for his loyalty, comic misunderstandings, and unexpected moments of insight.
  • B. Hazel
    "Hazel" is a song featured on Bob Dylan’s 1974 album Planet Waves.
  • C. Hazel
    Hazel is a classic American television sitcom from the 1960s centered on a witty live-in maid and the suburban family she works for.
  • D. Hazel
    Hazel is the given first name of American Baseball Hall of Famer Kiki Cuyler.
  • E. Lila
    Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d5820c8190a1ad6d6551d093bb completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95e68d1288190920c26cbfd396a21 completed April 10, 2026, 8:32 p.m.
NEDg Description generation batch_69d95f80d0c48190b88e3a4b3e42279c completed April 10, 2026, 8:37 p.m.
NED2 Entity disambiguation (via description) batch_69d9602748608190b0c971accf44b7aa completed April 10, 2026, 8:40 p.m.
Created at: April 6, 2026, 12:34 p.m.