Triple

T9315013
Position Surface form Disambiguated ID Type / Status
Subject Health Service Executive E224094 entity
Predicate abbreviation P43 FINISHED
Object HSE E791044 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: HSE | Statement: [Health Service Executive, abbreviation, HSE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HSE
Context triple: [Health Service Executive, abbreviation, HSE]
  • A. HSE chosen
    HSE is Ireland’s national public health and social care service provider responsible for delivering health services to everyone living in the country.
  • B. HSE
    HSE is a leading Russian research university known for its strong programs in economics, social sciences, and data analysis, with campuses in Moscow and several other major cities.
  • C. HSEMA
    HSEMA is the District of Columbia’s government agency responsible for coordinating homeland security, emergency preparedness, response, and recovery efforts in Washington, D.C.
  • D. OHSEPR
    OHSEPR is a U.S. federal office within the Department of Health and Human Services that coordinates emergency preparedness, response, and recovery efforts for human services programs and vulnerable populations.
  • E. HESG
    HESG is the ICAO airport code assigned to Sohag International Airport in Egypt.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd20b2274481908ddb4eda70cea8cc completed April 1, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3aa178881909e773e11c3892381 completed April 4, 2026, 10:10 a.m.
Created at: March 30, 2026, 7:37 p.m.