Triple

T4575465
Position Surface form Disambiguated ID Type / Status
Subject UTF-7 E123130 entity
Predicate hasMIMECharsetName P58058 FINISHED
Object UTF-7 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: UTF-7 | Statement: [UTF-7, hasMIMECharsetName, UTF-7]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMIMECharsetName
Context triple: [UTF-7, hasMIMECharsetName, UTF-7]
  • A. hasUnicode
    Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
  • B. hasTextualCharacter
    Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
  • C. usesCharacterSet
    Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
  • 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. hasContentType
    Indicates that an entity is associated with or classified by a specific type of content.
  • 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_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58dfe3508190b21836079e951a3c completed March 20, 2026, 2:25 p.m.
PD Predicate disambiguation batch_69bd5228b70c8190ac48705e35a710c1 completed March 20, 2026, 1:56 p.m.
PDg Predicate description generation batch_69bd56b4a9508190acdb888eef18f1ee completed March 20, 2026, 2:16 p.m.
Created at: March 20, 2026, 1:10 p.m.