Triple

T16906807
Position Surface form Disambiguated ID Type / Status
Subject Hebrew letter Ayin E424583 entity
Predicate hasCategoryInUnicode P125168 FINISHED
Object Letter, other 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: Letter, other | Statement: [Hebrew letter Ayin, hasCategoryInUnicode, Letter, other]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCategoryInUnicode
Context triple: [Hebrew letter Ayin, hasCategoryInUnicode, Letter, other]
  • A. hasUnicode
    Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
  • B. containsCategory
    Indicates that one entity includes or encompasses a specific category as part of its classification or organizational structure.
  • C. hasUnicodeName
    Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
  • D. hasBlockUnicode
    Indicates that one entity possesses or is associated with a specific Unicode block related to another entity.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3ca39f9b08190b15106c6caf895ec completed April 18, 2026, 6:15 p.m.
PD Predicate disambiguation batch_69e32b9489408190bcb2ede567ff5bf9 completed April 18, 2026, 6:58 a.m.
PDg Predicate description generation batch_69e34fb7c8c8819086975b7955b7d8ef completed April 18, 2026, 9:32 a.m.
Created at: April 10, 2026, 5:30 a.m.