Triple

T24007094
Position Surface form Disambiguated ID Type / Status
Subject Tanba Province E594417 entity
Predicate nameWrittenWithKanji P114914 FINISHED
Object 丹波国
丹波国 was an old province of Japan located in what is now central Kyoto and eastern Hyōgo Prefectures, known historically for its mountainous terrain and strategic position near the capital.
 E1614843 NE FINISHED

How this triple was built (3 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: 丹波国 | Statement: [Tanba Province, nameWrittenWithKanji, 丹波国]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: 丹波国
Triple: [Tanba Province, nameWrittenWithKanji, 丹波国]
Generated description
丹波国 was an old province of Japan located in what is now central Kyoto and eastern Hyōgo Prefectures, known historically for its mountainous terrain and strategic position near the capital.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: nameWrittenWithKanji
Context triple: [Tanba Province, nameWrittenWithKanji, 丹波国]
  • A. nameWrittenIn
    Indicates that an entity’s name is written or recorded using a specified language, script, or writing system.
  • B. hasNameInKanji chosen
    Indicates that an entity is associated with a specific written form of its name in Kanji characters.
  • C. nameLengthInKanji
    Indicates the number of kanji characters used in an entity’s name.
  • D. nameInJapaneseKana
    Indicates that an entity’s name is written or represented using Japanese kana characters.
  • E. nameLengthInKana
    Indicates the length of an entity’s name when written in kana characters.
  • F. None of above.

Provenance (6 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_69e288bc8f608190ac4af29f0bd1c744 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d46a6ba48190b0cce0b134dfb35f completed April 29, 2026, 9:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7e9b011c8190bc3ef5107aee5e35 completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7f4da3048190af7ef06dcec0a651 completed May 21, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f801bcc9c81908bbb270d7e762c11 completed May 21, 2026, 9:58 p.m.
PD Predicate disambiguation batch_69f17639d23c8190bed93434e2f9230a completed April 29, 2026, 3:08 a.m.
Created at: April 17, 2026, 9:40 p.m.