Triple

T33760584
Position Surface form Disambiguated ID Type / Status
Subject Labský důl E865094 entity
Predicate nameMeaning P453 FINISHED
Object Elbe Mine
Elbe Mine is a scenic glacial valley in the Krkonoše Mountains of the Czech Republic, known as the upper valley of the Elbe River and a popular destination for hiking and nature tourism.
E2064781 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: Elbe Mine | Statement: [Labský důl, nameMeaning, Elbe Mine]
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: Elbe Mine
Triple: [Labský důl, nameMeaning, Elbe Mine]
Generated description
Elbe Mine is a scenic glacial valley in the Krkonoše Mountains of the Czech Republic, known as the upper valley of the Elbe River and a popular destination for hiking and nature tourism.

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_69f3498d3b748190aa3c4006c1f32f38 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fc6130a88190aa23b826fc7c5266 completed May 3, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c995f188190b40b5eff42eff403 completed June 20, 2026, 9:25 a.m.
NEDg Description generation batch_6a365d1385648190a48b5817d3ec67f9 completed June 20, 2026, 9:27 a.m.
NED2 Entity disambiguation (via description) batch_6a365e46ab788190a9339c42340cccba completed June 20, 2026, 9:32 a.m.
Created at: May 1, 2026, 1:45 a.m.