Triple

T34823506
Position Surface form Disambiguated ID Type / Status
Subject Haguro E1003852 entity
Predicate sisterShip P3142 FINISHED
Object Ashigara
Ashigara is a Japanese Myōkō-class heavy cruiser that served in the Imperial Japanese Navy during the early 20th century, including World War II.
E2294652 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: Ashigara | Statement: [Haguro, sisterShip, Ashigara]
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: Ashigara
Triple: [Haguro, sisterShip, Ashigara]
Generated description
Ashigara is a Japanese Myōkō-class heavy cruiser that served in the Imperial Japanese Navy during the early 20th century, including World War II.

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_69f76db717088190811b4e744610f37d completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77adf71d88190812e930bcf1e2ce5 completed May 3, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c0994d2588190a0235276c81bef47 completed Aug. 12, 2026, 5:50 a.m.
NEDg Description generation batch_6a7c0a04af8c8190bf8f6a839ae71ac4 completed Aug. 12, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a7c0a521ae88190956fe64d46a8c481 completed Aug. 12, 2026, 5:53 a.m.
Created at: May 3, 2026, 4 p.m.