Triple

T8158375
Position Surface form Disambiguated ID Type / Status
Subject Zhuang people E190509 entity
Predicate historicalWritingSystem P1558 FINISHED
Object Sawndip E545685 NE 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: Sawndip | Statement: [Zhuang people, historicalWritingSystem, Sawndip]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sawndip
Context triple: [Zhuang people, historicalWritingSystem, Sawndip]
  • A. Sawndip chosen
    Sawndip is the traditional logographic script used for writing the Zhuang language, based largely on adapted Chinese characters.
  • B. Parchal
    Parchal is a town in Portugal’s Algarve region, situated near the Arade River opposite Portimão and known historically for its fishing and canning industries.
  • C. Bhailsa
    Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
  • D. Sawerigadi
    Sawerigadi is a town in Indonesia located in the province of Southeast Sulawesi.
  • E. Sawanih
    Sawanih is a notable literary work by the Indian poet Faizi, recognized for its contribution to classical Persian literature in South Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb455213f08190a4327a2116c7381f completed March 31, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf21ab2c8190af23b4a3a4bdb543 completed April 1, 2026, 6:45 a.m.
Created at: March 30, 2026, 5:38 p.m.