Triple

T17111830
Position Surface form Disambiguated ID Type / Status
Subject Latn E415243 entity
Predicate hasUnicodeScriptName P125990 FINISHED
Object Latin LITERAL 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: Latin | Statement: [Latn, hasUnicodeScriptName, Latin]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUnicodeScriptName
Context triple: [Latn, hasUnicodeScriptName, Latin]
  • A. hasUnicodeScript
    Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
  • B. hasUnicodeName
    Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
  • C. hasUnicode
    Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
  • D. hasUnicodeStandard
    Indicates that something conforms to, is defined by, or is associated with a particular version or aspect of the Unicode standard.
  • E. hasUnicodeStatus
    Indicates that a given entity has a particular Unicode-related classification or status (such as assigned, reserved, deprecated, or noncharacter) within the Unicode standard.
  • F. None of above. chosen

Provenance (4 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2bab0881908339ec7fb3ebe7e9 completed April 18, 2026, 7:31 p.m.
PD Predicate disambiguation batch_69e35d6b1b988190a8d6b6fe78c35e59 completed April 18, 2026, 10:31 a.m.
PDg Predicate description generation batch_69e37542d060819082aa73948eb8ebd4 completed April 18, 2026, 12:12 p.m.
Created at: April 10, 2026, 5:35 a.m.