Triple

T30249002
Position Surface form Disambiguated ID Type / Status
Subject Bingen (Baden) E769140 entity
Predicate locatedInRegion P40 FINISHED
Object southwestern Baden-Württemberg
Southwestern Baden-Württemberg is a region in the southwest of the German state of Baden-Württemberg, characterized by its proximity to the Upper Rhine and the Black Forest.
E1907538 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: southwestern Baden-Württemberg | Statement: [Bingen (Baden), locatedInRegion, southwestern Baden-Württemberg]
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: southwestern Baden-Württemberg
Triple: [Bingen (Baden), locatedInRegion, southwestern Baden-Württemberg]
Generated description
Southwestern Baden-Württemberg is a region in the southwest of the German state of Baden-Württemberg, characterized by its proximity to the Upper Rhine and the Black Forest.

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_69f224831dc08190b2e569b987264057 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68079a50c819090a11d215f3dd4b0 completed May 2, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276eee51c0819083fb237912efe2d5 completed June 9, 2026, 1:39 a.m.
NEDg Description generation batch_6a276fa88d248190a7bc70990a19ba5a completed June 9, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a277064150c8190a1d43e89ec3c4886 completed June 9, 2026, 1:46 a.m.
Created at: April 29, 2026, 7:40 p.m.