Triple

T14703665
Position Surface form Disambiguated ID Type / Status
Subject Chief Tui E345368 entity
Predicate relatedTo P37 FINISHED
Object Sina unclear NED1 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: Sina | Statement: [Chief Tui, relatedTo, Sina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sina
Context triple: [Chief Tui, relatedTo, Sina]
  • A. Sina
    Sina is a given name and surname used in various cultures, often associated with notable figures in fields such as science, arts, and media.
  • B. Shina
    Shina is an Indo-Aryan language spoken primarily in the Gilgit-Baltistan region of Pakistan and surrounding Himalayan areas.
  • C. Tsien
    Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
  • D. Qimei
    Qimei is the given name of Chen Qimei, an influential early Chinese revolutionary and close associate of Sun Yat-sen.
  • E. Tsinan
    Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cdfb09481908021a3fc92962a00 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:28 a.m.