Triple

T24839604
Position Surface form Disambiguated ID Type / Status
Subject Zagreb region E621578 entity
Predicate nearMountainRange P651 FINISHED
Object Medvednica
Medvednica is a forested mountain in northern Croatia known for overlooking the capital city of Zagreb and serving as a popular destination for hiking, skiing, and outdoor recreation.
E1654221 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: Medvednica | Statement: [Zagreb region, nearMountainRange, Medvednica]
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: Medvednica
Triple: [Zagreb region, nearMountainRange, Medvednica]
Generated description
Medvednica is a forested mountain in northern Croatia known for overlooking the capital city of Zagreb and serving as a popular destination for hiking, skiing, and outdoor recreation.

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_69e2fac185d48190a0a6073ad1f6b792 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422c7d3b08190a7d7e660f227a4f7 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c4d268081908fa119333d0ec727 completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a102814f838819094ed41d653039f72 completed May 22, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_6a10294485508190a91d9ec391181047 completed May 22, 2026, 10 a.m.
Created at: April 18, 2026, 5:18 a.m.