Triple

T14410036
Position Surface form Disambiguated ID Type / Status
Subject 400 Degreez E357298 entity
Predicate hasPart P35 FINISHED
Object Ha
"Ha" is a track by rapper Juvenile, notable for its distinctive second-person narrative style and repetitive use of the word "ha," from his influential 1998 album *400 Degreez*.
 E1098120 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: Ha | Statement: [400 Degreez, hasPart, Ha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ha
Context triple: [400 Degreez, hasPart, Ha]
  • A. Ho
    Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
  • B. Ho
    "Ho" is a track featured on Ludacris's debut studio album "Back for the First Time."
  • C. Ho
    Ho are an indigenous Adivasi community of eastern India, primarily inhabiting parts of Jharkhand and Odisha, known for their Austroasiatic Ho language and distinct cultural traditions.
  • D. Ho
    Ho is a town in southeastern Ghana that serves as the capital of the Volta Region and an important administrative and commercial center.
  • E. Ho
    Ho is a common East Asian surname used in various cultures, including Chinese and Korean, often representing different characters and lineages depending on the language and region.
  • 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: Ha
Triple: [400 Degreez, hasPart, Ha]
Generated description
"Ha" is a track by rapper Juvenile, notable for its distinctive second-person narrative style and repetitive use of the word "ha," from his influential 1998 album *400 Degreez*.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ha
Target entity description: "Ha" is a track by rapper Juvenile, notable for its distinctive second-person narrative style and repetitive use of the word "ha," from his influential 1998 album *400 Degreez*.
  • A. Ho
    Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
  • B. Ho
    Ho are an indigenous Adivasi community of eastern India, primarily inhabiting parts of Jharkhand and Odisha, known for their Austroasiatic Ho language and distinct cultural traditions.
  • C. Ho
    Ho is a town in southeastern Ghana that serves as the capital of the Volta Region and an important administrative and commercial center.
  • D. Ho
    Ho is a common East Asian surname used in various cultures, including Chinese and Korean, often representing different characters and lineages depending on the language and region.
  • E. Ho
    "Ho" is a track featured on Ludacris's debut studio album "Back for the First Time."
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90c9b3448190aec1608836a5e913 completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55269d8c81909592277741a93db6 completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd58216a8c8190b1fffcb670f15e16 completed May 8, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69fd589144b8819099aadef126b8728f completed May 8, 2026, 3:29 a.m.
Created at: April 10, 2026, 1:17 a.m.