Triple

T8408268
Position Surface form Disambiguated ID Type / Status
Subject Windsor County, Vermont E198556 entity
Predicate traversedByRiver P165 FINISHED
Object White River
The White River is a tributary of the Connecticut River in central Vermont, known for its clear waters, trout fishing, and scenic valleys along its course.
E482315 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: White River | Statement: [Windsor County, Vermont, traversedByRiver, White 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: White River
Triple: [Windsor County, Vermont, traversedByRiver, White River]
Generated description
The White River is a tributary of the Connecticut River in central Vermont, known for its clear waters, trout fishing, and scenic valleys along its course.

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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb8315a8a8819097f6da11b909b527 completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a79ca51842081909dc2ed83bd8815d4 completed Aug. 10, 2026, 12:55 p.m.
NEDg Description generation batch_6a79cb07a48081908e49cadd8485d764 completed Aug. 10, 2026, 12:58 p.m.
NED2 Entity disambiguation (via description) batch_6a79cbdc12f0819080a8e3efa832ccd3 completed Aug. 10, 2026, 1:02 p.m.
Created at: March 30, 2026, 6:05 p.m.