Triple

T32989429
Position Surface form Disambiguated ID Type / Status
Subject Mascoma Lake E844042 entity
Predicate locatedIn P40 FINISHED
Object western New Hampshire
Western New Hampshire is a region of the U.S. state of New Hampshire characterized by its rural landscapes, small towns, and numerous lakes and rivers near the Vermont border.
E723376 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: western New Hampshire | Statement: [Mascoma Lake, locatedIn, western 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: western New Hampshire
Triple: [Mascoma Lake, locatedIn, western New Hampshire]
Generated description
Western New Hampshire is a region of the U.S. state of New Hampshire characterized by its rural landscapes, small towns, and numerous lakes and rivers near the Vermont border.

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_69f3494d99988190b502c68926af2c4d completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d212e0b08190891229dff46e7ca7 completed May 3, 2026, 4:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34dac2ea9481909e110a64206e2b63 completed June 19, 2026, 5:59 a.m.
NEDg Description generation batch_6a34db6329708190a5dfa86c7b717094 completed June 19, 2026, 6:02 a.m.
NED2 Entity disambiguation (via description) batch_6a34dc60dfcc819089a4abdaebeb4dd6 completed June 19, 2026, 6:06 a.m.
Created at: May 1, 2026, 1:22 a.m.