Triple

T31039552
Position Surface form Disambiguated ID Type / Status
Subject Dresden, Ohio E790950 entity
Predicate locatedNearConfluenceOf P11842 FINISHED
Object Wakatomika Creek
Wakatomika Creek is a stream in central Ohio that serves as a tributary of the Muskingum River and flows through rural communities and farmland.
E2295324 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: Wakatomika Creek | Statement: [Dresden, Ohio, locatedNearConfluenceOf, Wakatomika Creek]
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: Wakatomika Creek
Triple: [Dresden, Ohio, locatedNearConfluenceOf, Wakatomika Creek]
Generated description
Wakatomika Creek is a stream in central Ohio that serves as a tributary of the Muskingum River and flows through rural communities and farmland.

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_69f224ca2fa881908a3ac5fedf207b90 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f694f8cc988190b8e6e87a9d1f7d41 completed May 3, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d3c343d988190b2b686de4642fb80 completed Aug. 13, 2026, 3:38 a.m.
NEDg Description generation batch_6a7d3c91e7548190baa12d37e25dbc92 completed Aug. 13, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a7d3d2c73fc81908c2ecaa4a3890077 completed Aug. 13, 2026, 3:42 a.m.
Created at: April 29, 2026, 8:59 p.m.