Triple

T33147402
Position Surface form Disambiguated ID Type / Status
Subject Minija River E848339 entity
Predicate hasTributary P415 FINISHED
Object Pateklė River
Pateklė River is a smaller watercourse in western Lithuania that serves as one of the tributaries feeding the Minija River.
E2037759 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: Pateklė River | Statement: [Minija River, hasTributary, Pateklė 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: Pateklė River
Triple: [Minija River, hasTributary, Pateklė River]
Generated description
Pateklė River is a smaller watercourse in western Lithuania that serves as one of the tributaries feeding the Minija River.

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_69f3495a458c8190a1d34b237ba0be3f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d88ffa6081909b64a7014108abc7 completed May 3, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35162ad5bc81909e6af8ea1f043d26 completed June 19, 2026, 10:12 a.m.
NEDg Description generation batch_6a35172821448190ad3f02d03d3572c4 completed June 19, 2026, 10:17 a.m.
NED2 Entity disambiguation (via description) batch_6a35185b9a948190a738f8e2e95fd01e completed June 19, 2026, 10:22 a.m.
Created at: May 1, 2026, 1:28 a.m.