Triple

T24403743
Position Surface form Disambiguated ID Type / Status
Subject River Eden (Fife) E615248 entity
Predicate hasCrossing P416 FINISHED
Object Dairsie Bridge
Dairsie Bridge is a historic stone bridge in Fife, Scotland, notable for its medieval architecture and role in crossing the River Eden near the village of Dairsie.
E1659705 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: Dairsie Bridge | Statement: [River Eden (Fife), hasCrossing, Dairsie Bridge]
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: Dairsie Bridge
Triple: [River Eden (Fife), hasCrossing, Dairsie Bridge]
Generated description
Dairsie Bridge is a historic stone bridge in Fife, Scotland, notable for its medieval architecture and role in crossing the River Eden near the village of Dairsie.

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_69e2d7e780bc81908049c779e697a7f6 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f294dcf7f4819094d2a3be163a5822 completed April 29, 2026, 11:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1032e0edd081908c131d8c42d23f8e completed May 22, 2026, 10:41 a.m.
NEDg Description generation batch_6a1034e935a08190ad56690d23338eca completed May 22, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a10357df90081909f85803c49475ed8 completed May 22, 2026, 10:52 a.m.
Created at: April 18, 2026, 2:05 a.m.