Triple

T36146739
Position Surface form Disambiguated ID Type / Status
Subject Slovenski Javornik–Rijeka railway E1045472 entity
Predicate connects P390 FINISHED
Object Slovenski Javornik
Slovenski Javornik is a settlement in the Municipality of Jesenice in northwestern Slovenia, known historically for its ironworks and its position on important regional transport routes.
E2171533 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: Slovenski Javornik | Statement: [Slovenski Javornik–Rijeka railway, connects, Slovenski Javornik]
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: Slovenski Javornik
Triple: [Slovenski Javornik–Rijeka railway, connects, Slovenski Javornik]
Generated description
Slovenski Javornik is a settlement in the Municipality of Jesenice in northwestern Slovenia, known historically for its ironworks and its position on important regional transport routes.

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_69f76e37ace88190a906b107d388f5d1 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b35fb09c8190b6ba9b28a6a7f5e6 completed May 3, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d4acba88190aed90daed14a0f75 completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a390dedf15c819089930dbade349fbc completed June 22, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_6a390f02997881909c5588ca5ad3426a completed June 22, 2026, 10:31 a.m.
Created at: May 3, 2026, 4:08 p.m.