Triple

T26939136
Position Surface form Disambiguated ID Type / Status
Subject Polhov Gradec Hills E678463 entity
Predicate hasSettlement P1068 FINISHED
Object Polhov Gradec
Polhov Gradec is a small settlement in central Slovenia known for its picturesque rural setting beneath the Polhov Gradec Hills and its historic parish church and manor.
E1772133 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: Polhov Gradec | Statement: [Polhov Gradec Hills, hasSettlement, Polhov Gradec]
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: Polhov Gradec
Triple: [Polhov Gradec Hills, hasSettlement, Polhov Gradec]
Generated description
Polhov Gradec is a small settlement in central Slovenia known for its picturesque rural setting beneath the Polhov Gradec Hills and its historic parish church and manor.

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_69eeeb4d69588190a7c912164a1c37b3 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62051d4388190a043bae51a734e8d completed May 2, 2026, 4:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b21a893c819099e6b4a1ddfd7d1b completed May 24, 2026, 8:08 a.m.
NEDg Description generation batch_6a12b3e7b5208190b37ac7993cdc90b2 completed May 24, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_6a12b456bad48190b232cd4968f2b041 completed May 24, 2026, 8:18 a.m.
Created at: April 27, 2026, 6:17 a.m.