Triple

T8369915
Position Surface form Disambiguated ID Type / Status
Subject Dai La Citadel E197426 entity
Predicate hasAlternativeName P39 FINISHED
Object Thành Đại La E48177 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: Thành Đại La | Statement: [Dai La Citadel, hasAlternativeName, Thành Đại La]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thành Đại La
Context triple: [Dai La Citadel, hasAlternativeName, Thành Đại La]
  • A. Đông Đô chosen
    Đông Đô was a historical name for the city now known as Hanoi, which has long served as a major political and cultural center of Vietnam.
  • B. Guandu
    Guandu is a district in northern Taipei, Taiwan, known for its riverside wetlands, hot springs, and the historic Guandu Temple.
  • C. Da Yuan
    Da Yuan is the official Chinese name for the Yuan dynasty, the Mongol-ruled imperial dynasty that governed China from the late 13th to the mid-14th century.
  • D. Longcheng
    Longcheng was the principal royal city and political center of the Xiongnu confederation in ancient Inner Asia.
  • E. Ganlu
    Ganlu was a historical Chinese era name used during the Cao Wei state of the Three Kingdoms period.
  • 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_69ca82f56730819080cec5d991c76f4c completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb80a400888190bef114052f3c4f76 completed March 31, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc7929e388190b35505378d0cf653 completed April 2, 2026, 1:34 a.m.
Created at: March 30, 2026, 6:01 p.m.