Triple

T29104809
Position Surface form Disambiguated ID Type / Status
Subject Winslow, Bainbridge Island E736732 entity
Predicate hasNearbyWaterBody P1489 FINISHED
Object Eagle Harbor
Eagle Harbor is a sheltered bay and marina on Bainbridge Island in Washington State, known as a key local waterfront and ferry terminal area facing Puget Sound.
E1855955 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: Eagle Harbor | Statement: [Winslow, Bainbridge Island, hasNearbyWaterBody, Eagle 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: Eagle Harbor
Triple: [Winslow, Bainbridge Island, hasNearbyWaterBody, Eagle Harbor]
Generated description
Eagle Harbor is a sheltered bay and marina on Bainbridge Island in Washington State, known as a key local waterfront and ferry terminal area facing Puget Sound.

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_69f077ec765c81909474c88bcc8bab43 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f661b93fe48190b846fb7654dc7b7d completed May 2, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2569a663e88190b671dfe56353dd70 completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a256dc27c708190b74c697d4eb1f0a2 completed June 7, 2026, 1:10 p.m.
NED2 Entity disambiguation (via description) batch_6a257303ae008190aad081788fc11925 completed June 7, 2026, 1:32 p.m.
Created at: April 28, 2026, 11:14 a.m.