Triple

T15855380
Position Surface form Disambiguated ID Type / Status
Subject Casco, Maine E384439 entity
Predicate hasBodyOfWater P1778 FINISHED
Object Pleasant Lake
Pleasant Lake is a scenic freshwater lake located in the town of Casco in southern Maine, known for recreation and lakeside camps.
E2038914 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: Pleasant Lake | Statement: [Casco, Maine, hasBodyOfWater, Pleasant Lake]
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: Pleasant Lake
Triple: [Casco, Maine, hasBodyOfWater, Pleasant Lake]
Generated description
Pleasant Lake is a scenic freshwater lake located in the town of Casco in southern Maine, known for recreation and lakeside camps.

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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14caf6ae481909ae1385cb4548612 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3515ef21dc8190a720da87ed78dd1f completed June 19, 2026, 10:11 a.m.
NEDg Description generation batch_6a3516b1daa08190a21764ce7125ec69 completed June 19, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_6a35172e773881908a625df198825ef0 completed June 19, 2026, 10:17 a.m.
Created at: April 10, 2026, 4:50 a.m.