Triple

T29255634
Position Surface form Disambiguated ID Type / Status
Subject Beaulieu Abbey E741695 entity
Predicate adjacentTo P224 FINISHED
Object Beaulieu River
The Beaulieu River is a picturesque tidal river in Hampshire, England, known for flowing through the New Forest and past the historic village and maritime attractions of Beaulieu.
E1954675 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: Beaulieu River | Statement: [Beaulieu Abbey, adjacentTo, Beaulieu River]
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: Beaulieu River
Triple: [Beaulieu Abbey, adjacentTo, Beaulieu River]
Generated description
The Beaulieu River is a picturesque tidal river in Hampshire, England, known for flowing through the New Forest and past the historic village and maritime attractions of Beaulieu.

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_69f0911eba2c8190b07cd2fdf91422c9 completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f664ad3f708190aa20d4224a218c8e completed May 2, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a296bb4f2948190a70981566595933e completed June 10, 2026, 1:50 p.m.
NEDg Description generation batch_6a296c9a1c4c81909c8fc4f25e4d0e6d completed June 10, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a29c642277c819081131c5da71c8ce2 completed June 10, 2026, 8:17 p.m.
Created at: April 28, 2026, 12:37 p.m.