Triple

T33023937
Position Surface form Disambiguated ID Type / Status
Subject Newfound Lake E844986 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Bristol, New Hampshire
Bristol, New Hampshire is a small New England town in Grafton County known for its scenic setting near Newfound Lake and outdoor recreational opportunities.
E367722 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: Bristol, New Hampshire | Statement: [Newfound Lake, hasNearbySettlement, Bristol, New Hampshire]
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: Bristol, New Hampshire
Triple: [Newfound Lake, hasNearbySettlement, Bristol, New Hampshire]
Generated description
Bristol, New Hampshire is a small New England town in Grafton County known for its scenic setting near Newfound Lake and outdoor recreational opportunities.

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_69f34950749c8190ae05cd27adb16d58 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d2d7593481908ab40f9975dac00d completed May 3, 2026, 4:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5cd1fe4a088190831c50d60d4cbc9c completed July 19, 2026, 1:32 p.m.
NEDg Description generation batch_6a5cd2c479188190ad94a273b5d6c4bd completed July 19, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_6a5cd3dea28c8190a037c66f1ea7fc16 completed July 19, 2026, 1:40 p.m.
Created at: May 1, 2026, 1:23 a.m.