Triple

T20264920
Position Surface form Disambiguated ID Type / Status
Subject HMS Forester E498940 entity
Predicate pennantNumber P3153 FINISHED
Object H74
H74 was the pennant number of HMS Forester, a Royal Navy destroyer that served during the early to mid-20th century, including World War II.
E1420235 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: H74 | Statement: [HMS Forester, pennantNumber, H74]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: H74
Context triple: [HMS Forester, pennantNumber, H74]
  • A. HS748
    HS748 is a British twin-engine turboprop airliner designed for short-haul regional passenger and cargo operations.
  • B. H4T
    H4T is a Canadian postal code prefix associated with the Saint-Laurent borough of Montreal, Quebec.
  • C. H.702
    H.702 is an ITU-T recommendation that defines requirements and frameworks for IPTV terminal devices and related multimedia services.
  • D. H247
    H247 is the internal model code for the second-generation Mercedes-Benz GLA compact luxury crossover SUV.
  • E. H.430
    H.430 is an ITU-T multimedia communication standard developed by Study Group 16, typically addressing technical requirements for audiovisual services over telecommunications networks.
  • 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: H74
Triple: [HMS Forester, pennantNumber, H74]
Generated description
H74 was the pennant number of HMS Forester, a Royal Navy destroyer that served during the early to mid-20th century, including World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: H74
Target entity description: H74 was the pennant number of HMS Forester, a Royal Navy destroyer that served during the early to mid-20th century, including World War II.
  • A. HS748
    HS748 is a British twin-engine turboprop airliner designed for short-haul regional passenger and cargo operations.
  • B. H4T
    H4T is a Canadian postal code prefix associated with the Saint-Laurent borough of Montreal, Quebec.
  • C. H.702
    H.702 is an ITU-T recommendation that defines requirements and frameworks for IPTV terminal devices and related multimedia services.
  • D. H247
    H247 is the internal model code for the second-generation Mercedes-Benz GLA compact luxury crossover SUV.
  • E. H.430
    H.430 is an ITU-T multimedia communication standard developed by Study Group 16, typically addressing technical requirements for audiovisual services over telecommunications networks.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e674ce27688190b31d7a6c98d3ec5e completed April 20, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08553381308190b02328d2bc95fa89 completed May 16, 2026, 11:29 a.m.
NEDg Description generation batch_6a0855fad28c81908c1516b64b8b1dc8 completed May 16, 2026, 11:33 a.m.
NED2 Entity disambiguation (via description) batch_6a08569e603881908e28fec3e8f5f5aa completed May 16, 2026, 11:35 a.m.
Created at: April 11, 2026, 11:41 p.m.