Triple

T24761098
Position Surface form Disambiguated ID Type / Status
Subject Lorain E619441 entity
Predicate hasRecreationArea P5383 FINISHED
Object Black River Landing
Black River Landing is a waterfront event and recreation venue in Lorain, Ohio, known for hosting concerts, festivals, and community gatherings along the Black River.
E1653337 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: Black River Landing | Statement: [Lorain, hasRecreationArea, Black River Landing]
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: Black River Landing
Triple: [Lorain, hasRecreationArea, Black River Landing]
Generated description
Black River Landing is a waterfront event and recreation venue in Lorain, Ohio, known for hosting concerts, festivals, and community gatherings along the Black River.

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_69e2fabbea94819092ed41348909622f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4107c1e088190b2262059a50d1b6b completed May 1, 2026, 2:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c1008708190a48a1c4755381f45 completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a1028468998819087e3f9b72b85b947 completed May 22, 2026, 9:56 a.m.
NED2 Entity disambiguation (via description) batch_6a10291de8b081908ee2e532ddca698e completed May 22, 2026, 9:59 a.m.
Created at: April 18, 2026, 4:27 a.m.