Triple

T22739702
Position Surface form Disambiguated ID Type / Status
Subject Ossipee River E562374 entity
Predicate hasTributary P415 FINISHED
Object Bearcamp River
Bearcamp River is a river in eastern New Hampshire that flows through the Lakes Region before joining the Ossipee River.
E1702123 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: Bearcamp River | Statement: [Ossipee River, hasTributary, Bearcamp 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: Bearcamp River
Triple: [Ossipee River, hasTributary, Bearcamp River]
Generated description
Bearcamp River is a river in eastern New Hampshire that flows through the Lakes Region before joining the Ossipee River.

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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797241588190be67db7a37a88f23 completed April 29, 2026, 3:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ec717f3081908d986acc335485e5 completed May 22, 2026, 11:53 p.m.
NEDg Description generation batch_6a10eddf8e008190a604d8c0db0fdd9d completed May 22, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a10efe2fc188190ab9d5e8276a1ef2f completed May 23, 2026, 12:08 a.m.
Created at: April 17, 2026, 3:23 p.m.