Triple

T1603696
Position Surface form Disambiguated ID Type / Status
Subject Hakka E34449 entity
Predicate hasWritingStandard P1587 FINISHED
Object Pha̍k-fa-sṳ
Pha̍k-fa-sṳ is a Latin-based orthography developed for writing the Hakka Chinese language, historically used by missionaries and scholars.
 E181223 NE FINISHED

How this triple was built (4 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: Pha̍k-fa-sṳ | Statement: [Hakka, hasWritingStandard, Pha̍k-fa-sṳ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pha̍k-fa-sṳ
Context triple: [Hakka, hasWritingStandard, Pha̍k-fa-sṳ]
  • A. Baybayin
    Baybayin is an ancient pre-colonial Philippine script used to write several native languages before the widespread adoption of the Latin alphabet.
  • B. Hanyu Pinyin
    Hanyu Pinyin is the official romanization system for Standard Mandarin Chinese, using the Latin alphabet to represent Chinese pronunciation.
  • C. Fus’ha
    Fus’ha is the standardized, formal variety of Arabic used in writing, education, media, and official communication across the Arab world.
  • D. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • E. Xuan
    Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Pha̍k-fa-sṳ
Triple: [Hakka, hasWritingStandard, Pha̍k-fa-sṳ]
Generated description
Pha̍k-fa-sṳ is a Latin-based orthography developed for writing the Hakka Chinese language, historically used by missionaries and scholars.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pha̍k-fa-sṳ
Target entity description: Pha̍k-fa-sṳ is a Latin-based orthography developed for writing the Hakka Chinese language, historically used by missionaries and scholars.
  • A. Baybayin
    Baybayin is an ancient pre-colonial Philippine script used to write several native languages before the widespread adoption of the Latin alphabet.
  • B. Hanyu Pinyin
    Hanyu Pinyin is the official romanization system for Standard Mandarin Chinese, using the Latin alphabet to represent Chinese pronunciation.
  • C. Fus’ha
    Fus’ha is the standardized, formal variety of Arabic used in writing, education, media, and official communication across the Arab world.
  • D. Hakka
    Hakka is a Sinitic language spoken primarily by the Hakka people across southern China and various overseas Chinese communities.
  • E. Xuan
    Xuan is a Vietnamese surname commonly used as a family name in Vietnam.
  • F. None of above. chosen

Provenance (5 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_69a885fea6a481909fe83ba6441f1774 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9094f96ec819090286c21b3dfddd5 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad46ae8ef08190acf018f1db4bfa7c completed March 8, 2026, 9:51 a.m.
NEDg Description generation batch_69ad4827c51c8190b07f4e07ba710c9d completed March 8, 2026, 9:57 a.m.
NED2 Entity disambiguation (via description) batch_69ad487f5ce08190a72efddc64bd496c completed March 8, 2026, 9:59 a.m.
Created at: March 4, 2026, 7:28 p.m.