Triple

T28207606
Position Surface form Disambiguated ID Type / Status
Subject Adur river basin E717073 entity
Predicate containsVillage P4011 FINISHED
Object Albourne
Albourne is a small rural village in West Sussex, England, situated in the South East countryside near the River Adur.
E1811500 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: Albourne | Statement: [Adur river basin, containsVillage, Albourne]
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: Albourne
Triple: [Adur river basin, containsVillage, Albourne]
Generated description
Albourne is a small rural village in West Sussex, England, situated in the South East countryside near the River Adur.

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_69efd6b826908190857e6e7dad74ed93 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6430ef8f08190a1a75c70ea8863aa completed May 2, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1607098dec8190bef1224695b0d509 completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a161448370c8190bb9552c8ff05361a completed May 26, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a1614b55d548190a6e013316a0078f2 completed May 26, 2026, 9:46 p.m.
Created at: April 27, 2026, 10:36 p.m.