Triple

T26158580
Position Surface form Disambiguated ID Type / Status
Subject Isleornsay E660038 entity
Predicate hasHarbour P3007 FINISHED
Object Isleornsay Harbour
Isleornsay Harbour is a sheltered coastal inlet and anchorage on the Isle of Skye in Scotland, known for serving the small village of Isleornsay and offering scenic views toward the surrounding islands.
E1747200 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: Isleornsay Harbour | Statement: [Isleornsay, hasHarbour, Isleornsay Harbour]
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: Isleornsay Harbour
Triple: [Isleornsay, hasHarbour, Isleornsay Harbour]
Generated description
Isleornsay Harbour is a sheltered coastal inlet and anchorage on the Isle of Skye in Scotland, known for serving the small village of Isleornsay and offering scenic views toward the surrounding islands.

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_69ee5bc5a9908190899d39ce95c6d215 completed April 26, 2026, 6:39 p.m.
NER Named-entity recognition batch_69f60c12d3708190ac08d8b7c8ff48a5 completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e711ab8819089b078f4387f7669 completed May 23, 2026, 9:38 p.m.
NEDg Description generation batch_6a121f5b854481908b2c1abbbdc7cc89 completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a121fd8924881909fe3b5e2eeb1a407 completed May 23, 2026, 9:44 p.m.
Created at: April 26, 2026, 8:29 p.m.