Triple

T35031887
Position Surface form Disambiguated ID Type / Status
Subject Vlorë County E1010803 entity
Predicate containsRoad P93805 FINISHED
Object Vlore–Sarande coastal road
The Vlore–Sarande coastal road is a scenic highway in southern Albania that winds along the Ionian Sea, renowned for its dramatic mountain passes, sea views, and access to popular Riviera beaches.
E2123240 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: Vlore–Sarande coastal road | Statement: [Vlorë County, containsRoad, Vlore–Sarande coastal road]
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: Vlore–Sarande coastal road
Triple: [Vlorë County, containsRoad, Vlore–Sarande coastal road]
Generated description
The Vlore–Sarande coastal road is a scenic highway in southern Albania that winds along the Ionian Sea, renowned for its dramatic mountain passes, sea views, and access to popular Riviera beaches.

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_69f76dcea02c81908542a223f6d5059f completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fe83c1a6108190992580bb4e537dde completed May 9, 2026, 12:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd2afc3081909fe8ff973dfd0e11 completed June 21, 2026, 10:30 a.m.
NEDg Description generation batch_6a37bdd99244819093669c98be46f903 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bfd6e5a48190b6bcc0b9860ad4bb completed June 21, 2026, 10:41 a.m.
Created at: May 3, 2026, 4:01 p.m.