Triple

T396620
Position Surface form Disambiguated ID Type / Status
Subject Ironbottom Sound E8996 entity
Predicate alsoKnownAs P39 FINISHED
Object Savo Sound
Savo Sound is an area of ocean off Guadalcanal in the Solomon Islands that became infamous as a major naval battleground during World War II.
 E52318 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: Savo Sound | Statement: [Ironbottom Sound, alsoKnownAs, Savo Sound]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Savo Sound
Context triple: [Ironbottom Sound, alsoKnownAs, Savo Sound]
  • A. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • B. Egegik
    Egegik is a dialect of the Central Alaskan Yup’ik language traditionally spoken in the Egegik region of southwestern Alaska.
  • C. Kattegat
    Kattegat is a shallow sea area and strait between Denmark and Sweden that forms a key maritime passage linking the North Sea with the Baltic Sea.
  • D. Gulf of Finland
    The Gulf of Finland is a long, narrow arm of the Baltic Sea bordered by Finland, Estonia, and Russia, leading eastward to the city of Saint Petersburg.
  • E. Nansen Sound
    Nansen Sound is a narrow Arctic waterway in the Canadian Arctic Archipelago, known for its harsh ice conditions and its role in polar exploration routes.
  • 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: Savo Sound
Triple: [Ironbottom Sound, alsoKnownAs, Savo Sound]
Generated description
Savo Sound is an area of ocean off Guadalcanal in the Solomon Islands that became infamous as a major naval battleground during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Savo Sound
Target entity description: Savo Sound is an area of ocean off Guadalcanal in the Solomon Islands that became infamous as a major naval battleground during World War II.
  • A. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • B. Egegik
    Egegik is a dialect of the Central Alaskan Yup’ik language traditionally spoken in the Egegik region of southwestern Alaska.
  • C. Kattegat
    Kattegat is a shallow sea area and strait between Denmark and Sweden that forms a key maritime passage linking the North Sea with the Baltic Sea.
  • D. Gulf of Finland
    The Gulf of Finland is a long, narrow arm of the Baltic Sea bordered by Finland, Estonia, and Russia, leading eastward to the city of Saint Petersburg.
  • E. Nansen Sound
    Nansen Sound is a narrow Arctic waterway in the Canadian Arctic Archipelago, known for its harsh ice conditions and its role in polar exploration routes.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec8a941081909a152fda0ce24a98 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b4695288190b4a7e67b6a112ca6 completed March 1, 2026, 10:56 a.m.
NEDg Description generation batch_69a41ef33c3c81909c8c9ce2964748ee completed March 1, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_69a4206a7ef8819086cf8c02f098551e completed March 1, 2026, 11:18 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.