Triple

T30803807
Position Surface form Disambiguated ID Type / Status
Subject Kruckenkreuz E784441 entity
Predicate hasUnicodeApproximation P181072 FINISHED
Object U+2629 (cross potent) 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: U+2629 (cross potent) | Statement: [Kruckenkreuz, hasUnicodeApproximation, U+2629 (cross potent)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUnicodeApproximation
Context triple: [Kruckenkreuz, hasUnicodeApproximation, U+2629 (cross potent)]
  • A. hasUnicode
    Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
  • B. hasUnicodeStandard
    Indicates that something conforms to, is defined by, or is associated with a particular version or aspect of the Unicode standard.
  • C. hasUnicodeVariant
    Indicates that one entity has an alternative representation or equivalent form in Unicode corresponding to the other entity.
  • D. 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.
  • E. hasUnicodeName
    Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
  • 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_69f224b3a7ec819096939414d103e31e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f760a35b988190904e6267553ad2fe completed May 3, 2026, 2:50 p.m.
PD Predicate disambiguation batch_69f75eb3d6f081908c933474eb359e3d completed May 3, 2026, 2:41 p.m.
PDg Predicate description generation batch_69f760a2a90c8190b8fbc55412ab752b completed May 3, 2026, 2:50 p.m.
Created at: April 29, 2026, 8:42 p.m.