Triple

T25899945
Position Surface form Disambiguated ID Type / Status
Subject Shingashi River E652582 entity
Predicate flowsThrough P225 FINISHED
Object Tsurugashima
Tsurugashima is a city in Saitama Prefecture, Japan, known as a suburban residential area within the Greater Tokyo region.
E2287876 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: Tsurugashima | Statement: [Shingashi River, flowsThrough, Tsurugashima]
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: Tsurugashima
Triple: [Shingashi River, flowsThrough, Tsurugashima]
Generated description
Tsurugashima is a city in Saitama Prefecture, Japan, known as a suburban residential area within the Greater Tokyo region.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6038843c481909a71270b5846ba65 completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5a39c5f374819084d3026bf2dedb70 completed July 17, 2026, 2:18 p.m.
NEDg Description generation batch_6a5a4118d71081908584d903fff7e0df completed July 17, 2026, 2:50 p.m.
NED2 Entity disambiguation (via description) batch_6a5a41da85bc8190b940acefe2d02eee completed July 17, 2026, 2:53 p.m.
Created at: April 22, 2026, 8:24 a.m.