Triple

T36158815
Position Surface form Disambiguated ID Type / Status
Subject Dungeness Lighthouse E1045814 entity
Predicate partOf P40 FINISHED
Object English Channel lighthouse system
The English Channel lighthouse system is a network of coastal beacons that guide maritime traffic safely through the busy and often hazardous waters between southern England and northern France.
E2171883 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: English Channel lighthouse system | Statement: [Dungeness Lighthouse, partOf, English Channel lighthouse system]
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: English Channel lighthouse system
Triple: [Dungeness Lighthouse, partOf, English Channel lighthouse system]
Generated description
The English Channel lighthouse system is a network of coastal beacons that guide maritime traffic safely through the busy and often hazardous waters between southern England and northern France.

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_69f76e38903c8190a52887620f90aabe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b4c96804819087815d0342a96930 completed May 3, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d5217e48190b91c3320e3c1aa58 completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a390e3d07e48190b3869fa5138dd840 completed June 22, 2026, 10:28 a.m.
NED2 Entity disambiguation (via description) batch_6a390f4f8d848190b72143928c888b70 completed June 22, 2026, 10:32 a.m.
Created at: May 3, 2026, 4:08 p.m.