Triple

T37829243
Position Surface form Disambiguated ID Type / Status
Subject HMS Broadsword E943150 entity
Predicate BrazilianName P62257 FINISHED
Object BNS Greenhalgh
BNS Greenhalgh is a Brazilian Navy frigate, originally commissioned as HMS Broadsword in the British Royal Navy before being transferred and renamed.
 E2285416 NE FINISHED

How this triple was built (3 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: BNS Greenhalgh | Statement: [HMS Broadsword, BrazilianName, BNS Greenhalgh]
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: BNS Greenhalgh
Triple: [HMS Broadsword, BrazilianName, BNS Greenhalgh]
Generated description
BNS Greenhalgh is a Brazilian Navy frigate, originally commissioned as HMS Broadsword in the British Royal Navy before being transferred and renamed.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: BrazilianName
Context triple: [HMS Broadsword, BrazilianName, BNS Greenhalgh]
  • A. nameInBrazil chosen
    Indicates that an entity is known or referred to by a particular name specifically in the context of Brazil.
  • B. nameInPortuguese
    Indicates that an entity is referred to by a specific name when expressed in the Portuguese language.
  • C. usedAsCharacterNameInBrazil
    Indicates that a name is specifically used as a character name in Brazilian media or cultural contexts.
  • D. nicknameInPortuguese
    Indicates that one entity is used as a nickname for another entity specifically in the Portuguese language.
  • E. countryNamePortuguese
    Indicates the Portuguese-language name assigned to a given country.
  • F. None of above.

Provenance (6 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_69f76eea4c8c8190a335aed5955cf2db completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbae559a8819086ef839973f8d9b2 completed May 6, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a45e4b938588190aa9cd524635fd083 completed July 2, 2026, 4:10 a.m.
NEDg Description generation batch_6a45eac1bde88190a366d8eaa38b89c6 completed July 2, 2026, 4:36 a.m.
NED2 Entity disambiguation (via description) batch_6a45eb7685d48190af5a26b894c84c9f completed July 2, 2026, 4:39 a.m.
PD Predicate disambiguation batch_69fbb1440fa08190abf25ba684f75b6e completed May 6, 2026, 9:23 p.m.
Created at: May 3, 2026, 4:19 p.m.