Triple

T23450489
Position Surface form Disambiguated ID Type / Status
Subject Fishing Bay E567764 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Hoopers Island
Hoopers Island is a small, remote chain of islands in Maryland’s Chesapeake Bay known for its historic watermen community and seafood industry, especially crabbing and oystering.
E1727772 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: Hoopers Island | Statement: [Fishing Bay, hasNearbySettlement, Hoopers Island]
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: Hoopers Island
Triple: [Fishing Bay, hasNearbySettlement, Hoopers Island]
Generated description
Hoopers Island is a small, remote chain of islands in Maryland’s Chesapeake Bay known for its historic watermen community and seafood industry, especially crabbing and oystering.

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_69e2458b4c888190b1d7998f9862a558 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a64d3e9c8190a2596b067c4f5061 completed April 29, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11bae6269c8190b6327ee490b18461 completed May 23, 2026, 2:34 p.m.
NEDg Description generation batch_6a11be5eaa64819093fca394daf91d90 completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf1dd27c8190b77577de860ac016 completed May 23, 2026, 2:52 p.m.
Created at: April 17, 2026, 5:52 p.m.