Triple

T34320974
Position Surface form Disambiguated ID Type / Status
Subject Inawashiro Lake E880733 entity
Predicate hasInflow P967 FINISHED
Object Nagase River
Nagase River is a river in Fukushima Prefecture, Japan, that serves as one of the main tributaries feeding Lake Inawashiro.
E2292487 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: Nagase River | Statement: [Inawashiro Lake, hasInflow, Nagase River]
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: Nagase River
Triple: [Inawashiro Lake, hasInflow, Nagase River]
Generated description
Nagase River is a river in Fukushima Prefecture, Japan, that serves as one of the main tributaries feeding Lake Inawashiro.

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_69f349b9cd508190a996a616903b3e6d completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7138d2b708190806ec06f0e7a58c5 completed May 3, 2026, 9:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a799c26e0388190a61eca393e19ddd8 completed Aug. 10, 2026, 9:38 a.m.
NEDg Description generation batch_6a799c9964e0819096dbcc88e71f8d1f completed Aug. 10, 2026, 9:40 a.m.
NED2 Entity disambiguation (via description) batch_6a799d04dfa881909b2b99cdea379fbf completed Aug. 10, 2026, 9:42 a.m.
Created at: May 1, 2026, 1:57 a.m.