Triple

T27520617
Position Surface form Disambiguated ID Type / Status
Subject Spree basin E694696 entity
Predicate containsRiver P165 FINISHED
Object Kleine Spree
Kleine Spree is a smaller tributary of the Spree River in eastern Germany, contributing to the Spree’s overall drainage basin.
E1820628 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: Kleine Spree | Statement: [Spree basin, containsRiver, Kleine Spree]
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: Kleine Spree
Triple: [Spree basin, containsRiver, Kleine Spree]
Generated description
Kleine Spree is a smaller tributary of the Spree River in eastern Germany, contributing to the Spree’s overall drainage basin.

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_69ef538550208190aa9de8e2cb260d93 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f2ba2b88190962819631042d02d completed May 2, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16415829148190b1f9b47b14fe85b8 completed May 27, 2026, 12:56 a.m.
NEDg Description generation batch_6a164240e9308190aa46c9b0745446b7 completed May 27, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_6a16467e0a3c8190aba09c9f0a65298c completed May 27, 2026, 1:18 a.m.
Created at: April 27, 2026, 1:21 p.m.