Triple

T1126832
Position Surface form Disambiguated ID Type / Status
Subject Unicode Consortium E24737 entity
Predicate oversees P46 FINISHED
Object Unicode Emoji List E3674 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: Unicode Emoji List | Statement: [Unicode Consortium, oversees, Unicode Emoji List]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unicode Emoji List
Context triple: [Unicode Consortium, oversees, Unicode Emoji List]
  • A. Unicode Character Database
    The Unicode Character Database is a comprehensive collection of machine-readable data files that define the properties, classifications, and behaviors of every character encoded in the Unicode Standard.
  • B. Unicode chosen
    Unicode is a universal character encoding standard that assigns unique code points to virtually all written scripts, symbols, and emojis used in modern computing.
  • C. Unicode Scalar Values
    Unicode Scalar Values are the set of valid Unicode code points (excluding surrogate code points) that uniquely identify abstract characters in the Unicode standard.
  • D. Supplementary Multilingual Plane
    The Supplementary Multilingual Plane is a range of Unicode code points (Plane 1) that contains historic scripts, musical notation, and various specialized characters beyond the Basic Multilingual Plane.
  • E. Unicode Technical Report #29
    Unicode Technical Report #29 is the specification that defines how to determine and segment user-perceived text elements (grapheme clusters), words, and sentences in Unicode text.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdc2718819094f5519ffb56993b completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac539fc3708190b0b3dec5d5c73a71 completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:44 p.m.