Triple

T30276166
Position Surface form Disambiguated ID Type / Status
Subject Usa River E769949 entity
Predicate riverSystem P1009 FINISHED
Object Wetter
The Wetter is a river in central Germany that serves as a tributary of the Nidda and ultimately the Main, flowing through the state of Hesse.
E1906948 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: Wetter | Statement: [Usa River, riverSystem, Wetter]
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: Wetter
Triple: [Usa River, riverSystem, Wetter]
Generated description
The Wetter is a river in central Germany that serves as a tributary of the Nidda and ultimately the Main, flowing through the state of Hesse.

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_69f224868fa8819099127eaf8855a28f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680d8bca081909be6f60e68aec958 completed May 2, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ef82df081908c7fe0986c0cc740 completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a276fbc1a7c8190baabedef642e6d23 completed June 9, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a27703697088190bbea27c5cbf929ae completed June 9, 2026, 1:45 a.m.
Created at: April 29, 2026, 7:44 p.m.