Triple

T188718
Position Surface form Disambiguated ID Type / Status
Subject Singapore E3670 entity
Predicate officialLanguage P236 FINISHED
Object Mandarin Chinese E7177 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: Mandarin Chinese | Statement: [Singapore, officialLanguage, Mandarin Chinese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandarin Chinese
Context triple: [Singapore, officialLanguage, Mandarin Chinese]
  • A. Standard Chinese chosen
    Standard Chinese is the official standardized form of the Chinese language, based primarily on the Beijing dialect of Mandarin and used as the national lingua franca of China.
  • B. Paipai language
    The Paipai language is an indigenous Yuman language spoken by the Paipai people of northern Baja California, Mexico, and is considered highly endangered.
  • C. China
    China is a vast East Asian country known for its long continuous civilization, large population, and major global economic and political influence.
  • D. Baybayin
    Baybayin is an ancient pre-colonial Philippine script used to write several native languages before the widespread adoption of the Latin alphabet.
  • E. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • 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_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a2594abeec8190a48f36817e647fcd completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a30287094c8190ad4669e856a29f6c completed Feb. 28, 2026, 2:58 p.m.
Created at: Feb. 28, 2026, 2:41 a.m.