Triple

T35528495
Position Surface form Disambiguated ID Type / Status
Subject Valbiska (Krk) E1026733 entity
Predicate hasRoute P4374 FINISHED
Object Valbiska–Lopar ferry route
The Valbiska–Lopar ferry route is a Croatian Adriatic Sea ferry connection linking the island of Krk with the island of Rab.
E2145826 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: Valbiska–Lopar ferry route | Statement: [Valbiska (Krk), hasRoute, Valbiska–Lopar ferry route]
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: Valbiska–Lopar ferry route
Triple: [Valbiska (Krk), hasRoute, Valbiska–Lopar ferry route]
Generated description
The Valbiska–Lopar ferry route is a Croatian Adriatic Sea ferry connection linking the island of Krk with the island of Rab.

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_69f797d07ab48190b3d2acee4b8b588d completed May 3, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3852e7f2c08190900446e5cc7f6aad completed June 21, 2026, 9:08 p.m.
NEDg Description generation batch_6a3853a42cc08190a7aaadb52b0a2893 completed June 21, 2026, 9:12 p.m.
NED2 Entity disambiguation (via description) batch_6a3854efb9dc8190af96eba84b8b0bc1 completed June 21, 2026, 9:17 p.m.
Created at: May 3, 2026, 4:04 p.m.