Triple

T35534027
Position Surface form Disambiguated ID Type / Status
Subject Fužine E1026879 entity
Predicate hasCave P10755 FINISHED
Object Vrelo Cave
Vrelo Cave is a small but scenic show cave near Fužine in Croatia, known for its easy accessibility and underground lake and formations.
E2146838 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: Vrelo Cave | Statement: [Fužine, hasCave, Vrelo Cave]
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: Vrelo Cave
Triple: [Fužine, hasCave, Vrelo Cave]
Generated description
Vrelo Cave is a small but scenic show cave near Fužine in Croatia, known for its easy accessibility and underground lake and formations.

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_69f76dff7e508190b28ceeee770dce23 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f797d3dfac8190a33a800ab12f1a0a completed May 3, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3852e9b2f481908ddf999b98bdf356 completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a3856c969348190afc2ec73fd8d8f28 completed June 21, 2026, 9:25 p.m.
NED2 Entity disambiguation (via description) batch_6a385720d3ac8190977a17e2ea0f4def completed June 21, 2026, 9:26 p.m.
Created at: May 3, 2026, 4:04 p.m.