Triple

T809901
Position Surface form Disambiguated ID Type / Status
Subject Pixel 8 E17519 entity
Predicate colorOption P60 FINISHED
Object Obsidian E80216 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: Obsidian | Statement: [Pixel 8, colorOption, Obsidian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Obsidian
Context triple: [Pixel 8, colorOption, Obsidian]
  • A. Obsidian chosen
    Obsidian is a dark, nearly black color variant commonly used as a sleek, premium finish for electronic devices such as smartphones.
  • B. Lapis Niger
    Lapis Niger is an ancient black stone shrine and inscribed pavement in Rome’s Forum Romanum, traditionally associated with early Roman religious or funerary practices and sometimes linked to the legendary king Romulus.
  • C. Talx
    Talx is a workforce solutions and employment verification company that operates as a subsidiary of the credit reporting agency Equifax.
  • D. Quartz
    Quartz is a digital news outlet known for its global business journalism, data-driven reporting, and mobile-first storytelling.
  • E. Black Stone
    The Black Stone is a revered Islamic relic set into the eastern corner of the Kaaba in Mecca, which pilgrims traditionally try to touch or kiss during the Hajj and Umrah rituals.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab26d36c8190800e98890b7ae08e completed March 1, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d8623248190a2306b23ea378534 completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.