Triple

T5795205
Position Surface form Disambiguated ID Type / Status
Subject Speaker of Parliament (Singapore) E128491 entity
Predicate style P87 FINISHED
Object Madam Speaker E4551 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: Madam Speaker | Statement: [Speaker of Parliament (Singapore), style, Madam Speaker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madam Speaker
Context triple: [Speaker of Parliament (Singapore), style, Madam Speaker]
  • A. Madam Speaker chosen
    "Madam Speaker" is the formal mode of address used for a woman serving as Speaker of the United States House of Representatives.
  • B. Madam President
    Madam President is the formal style of address used for a woman serving as President of the Senate in Belgium.
  • C. Madam President
    "Madam President" is the formal style of address used for a female President of the United States.
  • D. Madam President
    Madam President is the formal style of address used for a female head of state serving as President of Romania.
  • E. Mister Speaker
    Mister Speaker is the traditional formal address used for a male Speaker presiding over the United States House of Representatives.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a91c7788190936671bf816d3772 completed March 22, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c098286c1c8190b77cbaeda327dba4 completed March 23, 2026, 1:32 a.m.
Created at: March 22, 2026, 3:51 p.m.