Triple

T30886709
Position Surface form Disambiguated ID Type / Status
Subject Loddon Valley floodplain E786786 entity
Predicate locatedIn P40 FINISHED
Object River Loddon valley
River Loddon valley is a low-lying river valley in southern England characterized by its extensive floodplains, wetlands, and rural landscapes.
 E1937600 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: River Loddon valley | Statement: [Loddon Valley floodplain, locatedIn, River Loddon valley]
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: River Loddon valley
Triple: [Loddon Valley floodplain, locatedIn, River Loddon valley]
Generated description
River Loddon valley is a low-lying river valley in southern England characterized by its extensive floodplains, wetlands, and rural landscapes.

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_69f224bbfa7c81908448e0c261c523e3 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69206481881909e9f3d0e59c5b889 completed May 3, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e45a4f8c819096832f02d3366937 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e53bedfc8190b0e66f481b11a095 completed June 10, 2026, 4:17 a.m.
NED2 Entity disambiguation (via description) batch_6a28e5c57ebc8190ad3489b51d221021 completed June 10, 2026, 4:19 a.m.
Created at: April 29, 2026, 8:49 p.m.