Triple

T27997980
Position Surface form Disambiguated ID Type / Status
Subject Una-Sana Canton E707066 entity
Predicate hasRiver P165 FINISHED
Object Bliha River
The Bliha River is a tributary watercourse in northwestern Bosnia and Herzegovina, known for flowing through the Una-Sana Canton and featuring scenic landscapes and waterfalls.
E2285235 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: Bliha River | Statement: [Una-Sana Canton, hasRiver, Bliha 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: Bliha River
Triple: [Una-Sana Canton, hasRiver, Bliha River]
Generated description
The Bliha River is a tributary watercourse in northwestern Bosnia and Herzegovina, known for flowing through the Una-Sana Canton and featuring scenic landscapes and waterfalls.

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_69ef96b980d88190a753b2f9a978595a completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63baca76c8190aa08543d74060334 completed May 2, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4560c01e0881909be5002ca9b2707f completed July 1, 2026, 6:47 p.m.
NEDg Description generation batch_6a457025a6188190ac54821ae19cdf5d completed July 1, 2026, 7:53 p.m.
NED2 Entity disambiguation (via description) batch_6a45913132248190935a23be2ece2aa6 completed July 1, 2026, 10:14 p.m.
Created at: April 27, 2026, 7:54 p.m.