Triple

T24072914
Position Surface form Disambiguated ID Type / Status
Subject Stjørdalselva E596283 entity
Predicate hasTributary P415 FINISHED
Object Tømmeråa
Tømmeråa is a river in Trøndelag county, Norway, known as one of the tributaries feeding into the larger Stjørdalselva river system.
E1675792 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: Tømmeråa | Statement: [Stjørdalselva, hasTributary, Tømmeråa]
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: Tømmeråa
Triple: [Stjørdalselva, hasTributary, Tømmeråa]
Generated description
Tømmeråa is a river in Trøndelag county, Norway, known as one of the tributaries feeding into the larger Stjørdalselva river system.

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_69e288c3999c8190809b282a04813dec completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1db1aad248190a1d25c64cc5016eb completed April 29, 2026, 10:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10759fb6bc8190a5f1c2ec2f2dca6a completed May 22, 2026, 3:26 p.m.
NEDg Description generation batch_6a1076b9b58881908eb0b619471c3879 completed May 22, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_6a1077d01fa08190b5439eba879538ef completed May 22, 2026, 3:35 p.m.
Created at: April 17, 2026, 10:42 p.m.