Triple

T36019959
Position Surface form Disambiguated ID Type / Status
Subject North Falmouth Harbor E1041954 entity
Predicate isNear P350 FINISHED
Object Megansett Harbor
Megansett Harbor is a small coastal harbor in North Falmouth, Massachusetts, known for its sheltered waters, moorings, and recreational boating access to Buzzards Bay.
E2204136 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: Megansett Harbor | Statement: [North Falmouth Harbor, isNear, Megansett Harbor]
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: Megansett Harbor
Triple: [North Falmouth Harbor, isNear, Megansett Harbor]
Generated description
Megansett Harbor is a small coastal harbor in North Falmouth, Massachusetts, known for its sheltered waters, moorings, and recreational boating access to Buzzards Bay.

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_69f76e2b981881908e4e160607fa82eb completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ace21cf08190ad1d2f5335d03dd1 completed May 3, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e1606992c8190bb0396fba8b6e25f completed June 26, 2026, 6:02 a.m.
NEDg Description generation batch_6a3e16a50d8c819094deb898cab90904 completed June 26, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a3e1b4f74f48190b12de0f00e7ab8b9 completed June 26, 2026, 6:25 a.m.
Created at: May 3, 2026, 4:07 p.m.