Triple

T34759690
Position Surface form Disambiguated ID Type / Status
Subject Seerhein E1002029 entity
Predicate connects P390 FINISHED
Object Obersee
Obersee is the eastern, larger part of Lake Constance, a major freshwater lake in Central Europe bordered by Germany, Austria, and Switzerland.
E2262625 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: Obersee | Statement: [Seerhein, connects, Obersee]
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: Obersee
Triple: [Seerhein, connects, Obersee]
Generated description
Obersee is the eastern, larger part of Lake Constance, a major freshwater lake in Central Europe bordered by Germany, Austria, and Switzerland.

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_69f76db0fb30819096709d43f9a1f45f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a178c1c81908aedc566d8474713 completed May 3, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4193a773ec8190a95d8226361c03d7 completed June 28, 2026, 9:35 p.m.
NEDg Description generation batch_6a4194a73dcc8190a4bfba8dd33acd8c completed June 28, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a41956d0f208190be2322f18ed193cf completed June 28, 2026, 9:43 p.m.
Created at: May 3, 2026, 3:59 p.m.