Triple

T21349828
Position Surface form Disambiguated ID Type / Status
Subject Eigeltingen E526443 entity
Predicate locatedNear P294 FINISHED
Object A98 motorway corridor
The A98 motorway corridor is a planned and partially built German autobahn route in southern Baden-Württemberg intended to improve east–west traffic connections near the Swiss border.
E2287584 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: A98 motorway corridor | Statement: [Eigeltingen, locatedNear, A98 motorway corridor]
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: A98 motorway corridor
Triple: [Eigeltingen, locatedNear, A98 motorway corridor]
Generated description
The A98 motorway corridor is a planned and partially built German autobahn route in southern Baden-Württemberg intended to improve east–west traffic connections near the Swiss border.

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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8ad30512081909012ce318fa67679 completed April 22, 2026, 11:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a59fff23ab4819086a927e83730b621 completed July 17, 2026, 10:12 a.m.
NEDg Description generation batch_6a5a006063388190803f3435652a8988 completed July 17, 2026, 10:13 a.m.
NED2 Entity disambiguation (via description) batch_6a5a00bd617481908c1bfe999714ea55 completed July 17, 2026, 10:15 a.m.
Created at: April 16, 2026, 5:03 p.m.