Triple

T25032101
Position Surface form Disambiguated ID Type / Status
Subject Marianna, Pennsylvania E626874 entity
Predicate hasWatercourse P165 FINISHED
Object Ten Mile Creek
Ten Mile Creek is a stream in southwestern Pennsylvania that flows through the area of Marianna and ultimately feeds into the Monongahela River.
 E1969082 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: Ten Mile Creek | Statement: [Marianna, Pennsylvania, hasWatercourse, Ten Mile 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: Ten Mile Creek
Triple: [Marianna, Pennsylvania, hasWatercourse, Ten Mile Creek]
Generated description
Ten Mile Creek is a stream in southwestern Pennsylvania that flows through the area of Marianna and ultimately feeds into the Monongahela 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_69e2ff2a2c088190be513727ee8bfe78 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44f70b1648190ab00365f89262d73 completed May 1, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b560e2e5481908a5112fcb3d5905b completed June 12, 2026, 12:42 a.m.
NEDg Description generation batch_6a2b5740b1e88190af5cf79a09800fc8 completed June 12, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a2b5a4b8a9c8190a33f1916d94b808f completed June 12, 2026, 1 a.m.
Created at: April 18, 2026, 6:07 a.m.