Triple

T1498775
Position Surface form Disambiguated ID Type / Status
Subject President of the Republic of China E29746 entity
Predicate style P87 FINISHED
Object Mr. President E1156 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: Mr. President | Statement: [President of the Republic of China, style, Mr. President]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. President
Context triple: [President of the Republic of China, style, Mr. President]
  • A. Mr. President chosen
    "Mr. President" is the formal spoken address traditionally used for the sitting President of the United States.
  • B. Mr. President
    "Mr. President" is a formal style of address used for the President of Ecuador.
  • C. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
  • D. Mr. Vice President
    Mr. Vice President is the formal spoken and written title used to address the sitting Vice President of the United States.
  • E. Bon Voyage, Mr. President
    "Bon Voyage, Mr. President" is a short story by Gabriel García Márquez that follows an exiled Caribbean dictator facing illness, nostalgia, and political ghosts while living in Geneva.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6f0ce988190aafab4a6e0dfd710 completed March 1, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1cb19b708190a28b1a0037860202 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 8:12 p.m.