Triple

T7454116
Position Surface form Disambiguated ID Type / Status
Subject National Hospital for Neurology and Neurosurgery E172075 entity
Predicate alsoKnownAs P39 FINISHED
Object NHNN
NHNN is a leading UK specialist hospital dedicated to the diagnosis, treatment, and research of neurological and neurosurgical conditions.
 E665248 NE FINISHED

How this triple was built (4 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: NHNN | Statement: [National Hospital for Neurology and Neurosurgery, alsoKnownAs, NHNN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NHNN
Context triple: [National Hospital for Neurology and Neurosurgery, alsoKnownAs, NHNN]
  • A. NHNN
    NHNN is the Vietnamese abbreviation for the State Bank of Vietnam, the country’s central bank responsible for monetary policy and financial regulation.
  • B. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • C. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • D. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • E. HN
    HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: NHNN
Triple: [National Hospital for Neurology and Neurosurgery, alsoKnownAs, NHNN]
Generated description
NHNN is a leading UK specialist hospital dedicated to the diagnosis, treatment, and research of neurological and neurosurgical conditions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NHNN
Target entity description: NHNN is a leading UK specialist hospital dedicated to the diagnosis, treatment, and research of neurological and neurosurgical conditions.
  • A. NHNN
    NHNN is the Vietnamese abbreviation for the State Bank of Vietnam, the country’s central bank responsible for monetary policy and financial regulation.
  • B. NH
    NH is the official two-letter United States Postal Service abbreviation for the state of New Hampshire.
  • C. NH
    NH is the two-letter IATA airline designator assigned to All Nippon Airways, Japan’s largest airline.
  • D. HN
    HN is the station code used to identify RAF Honington, a Royal Air Force station in Suffolk, England.
  • E. HN
    HN is the two-letter ISO 3166-1 alpha-2 country code assigned to Honduras.
  • F. None of above. chosen

Provenance (5 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_69c68a66554c8190add75c65942c0317 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f3addd648190b618bfbffe08db2c completed March 27, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827bedc408190a9a77f293fb12762 completed March 28, 2026, 7:10 p.m.
NEDg Description generation batch_69c8290c62d0819080a1e1820364da88 completed March 28, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69c82958eddc8190ad1697969241ec39 completed March 28, 2026, 7:17 p.m.
Created at: March 27, 2026, 3:14 p.m.