Triple

T3373889
Position Surface form Disambiguated ID Type / Status
Subject Haki R. Madhubuti E71019 entity
Predicate givenName P17 FINISHED
Object Haki
Haki is the given name of Haki R. Madhubuti, a prominent African-American poet, publisher, and leading figure of the Black Arts Movement.
 E352246 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: Haki | Statement: [Haki R. Madhubuti, givenName, Haki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haki
Context triple: [Haki R. Madhubuti, givenName, Haki]
  • A. Haql
    Haql is a small coastal town in northwestern Saudi Arabia on the Red Sea's Gulf of Aqaba, known for its clear waters, coral reefs, and views of neighboring Egypt and Jordan.
  • B. Haqearu
    Haqearu is an indigenous Aymaran language spoken in the central highlands of Peru.
  • C. Haastrecht
    Haastrecht is a small historic town in the Dutch province of South Holland, known for its picturesque canalside setting and traditional Dutch architecture.
  • D. Hakitia
    Hakitia is a Judeo-Spanish dialect historically spoken by North African Sephardic Jews, blending Old Spanish with Hebrew and elements of Arabic.
  • E. Hau
    Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
  • 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: Haki
Triple: [Haki R. Madhubuti, givenName, Haki]
Generated description
Haki is the given name of Haki R. Madhubuti, a prominent African-American poet, publisher, and leading figure of the Black Arts Movement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haki
Target entity description: Haki is the given name of Haki R. Madhubuti, a prominent African-American poet, publisher, and leading figure of the Black Arts Movement.
  • A. Haql
    Haql is a small coastal town in northwestern Saudi Arabia on the Red Sea's Gulf of Aqaba, known for its clear waters, coral reefs, and views of neighboring Egypt and Jordan.
  • B. Haqearu
    Haqearu is an indigenous Aymaran language spoken in the central highlands of Peru.
  • C. Haastrecht
    Haastrecht is a small historic town in the Dutch province of South Holland, known for its picturesque canalside setting and traditional Dutch architecture.
  • D. Hakitia
    Hakitia is a Judeo-Spanish dialect historically spoken by North African Sephardic Jews, blending Old Spanish with Hebrew and elements of Arabic.
  • E. Hau
    Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2bf4ad88190a2c49dc30f323a13 completed March 8, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b33442f28c8190b48a662a5dd1bac3 completed March 12, 2026, 9:46 p.m.
NEDg Description generation batch_69b334bd2cf081908503cb4cbdfc998c completed March 12, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_69b33529b31c8190811a659df8c5d2d4 completed March 12, 2026, 9:50 p.m.
Created at: March 8, 2026, 3:13 p.m.