Triple

T22145591
Position Surface form Disambiguated ID Type / Status
Subject Mogielica E547278 entity
Predicate nearbyTown P3883 FINISHED
Object Słopnice
Słopnice is a village in southern Poland’s Lesser Poland Voivodeship, known for its picturesque location in the Beskid Wyspowy mountains.
E1747553 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: Słopnice | Statement: [Mogielica, nearbyTown, Słopnice]
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: Słopnice
Triple: [Mogielica, nearbyTown, Słopnice]
Generated description
Słopnice is a village in southern Poland’s Lesser Poland Voivodeship, known for its picturesque location in the Beskid Wyspowy mountains.

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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f097248190a8a3cdff1593b5b5 completed April 28, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e64ef3081908b39a3c83e4440f3 completed May 23, 2026, 9:38 p.m.
NEDg Description generation batch_6a121fa58ae08190b70faa7e3c81eae8 completed May 23, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a12203ee42c8190be6d4c4d9f0ec859 completed May 23, 2026, 9:46 p.m.
Created at: April 16, 2026, 8:33 p.m.