Triple

T13373839
Position Surface form Disambiguated ID Type / Status
Subject Whitney Houston (1985 album) E319133 entity
Predicate producer P490 FINISHED
Object Material E513769 NE FINISHED

How this triple was built (2 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: Material | Statement: [Whitney Houston (1985 album), producer, Material]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Material
Context triple: [Whitney Houston (1985 album), producer, Material]
  • A. Material chosen
    Material is an experimental New York-based band led by bassist Bill Laswell, known for its genre-blending fusion of funk, jazz, dub, and avant-garde music.
  • B. Material II
    Material II is a South African comedy film starring and co-written by comedian Riaad Moosa, serving as the sequel to his popular film Material.
  • C. Material Thangz
    "Material Thangz" is an R&B/funk song by The Deele, known for its smooth groove and mid-1980s urban contemporary sound.
  • D. Matter
    Matter is an open, IP-based smart home connectivity standard designed to ensure secure, reliable interoperability between devices and ecosystems from different manufacturers.
  • E. Mattertal
    Mattertal is a high alpine valley in the Swiss canton of Valais, known for its dramatic peaks including the Matterhorn and its popular mountaineering and ski resorts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcda64a48190b53243a763cd175b completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72684f3408190952d2619b6b8d241 completed May 3, 2026, 10:42 a.m.
Created at: April 9, 2026, 9:33 p.m.