Triple

T38461293
Position Surface form Disambiguated ID Type / Status
Subject North Brother E912458 entity
Predicate drainage P1559 FINISHED
Object Wassataquoik Stream
Wassataquoik Stream is a remote river in Maine’s Baxter State Park known for its rugged wilderness setting and role in draining the slopes of Mount Katahdin and surrounding peaks.
E2282667 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: Wassataquoik Stream | Statement: [North Brother, drainage, Wassataquoik Stream]
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: Wassataquoik Stream
Triple: [North Brother, drainage, Wassataquoik Stream]
Generated description
Wassataquoik Stream is a remote river in Maine’s Baxter State Park known for its rugged wilderness setting and role in draining the slopes of Mount Katahdin and surrounding peaks.

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_69f76e861d8c81908559031dc66e3c15 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcce06ec5c81909b91ecb894043338 completed May 7, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4223a4fdd0819081b660e67e48b4d0 completed June 29, 2026, 7:49 a.m.
NEDg Description generation batch_6a4224d634208190b2a329d1a82f1663 completed June 29, 2026, 7:55 a.m.
NED2 Entity disambiguation (via description) batch_6a4225416dc8819088085e17f8396781 completed June 29, 2026, 7:56 a.m.
Created at: May 3, 2026, 4:31 p.m.