Triple

T30808606
Position Surface form Disambiguated ID Type / Status
Subject Lamar River E784575 entity
Predicate hasTributary P415 FINISHED
Object Slough Creek
Slough Creek is a scenic stream in Yellowstone National Park known for its wildlife-rich meadows and excellent trout fishing.
E2295120 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: Slough Creek | Statement: [Lamar River, hasTributary, Slough 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: Slough Creek
Triple: [Lamar River, hasTributary, Slough Creek]
Generated description
Slough Creek is a scenic stream in Yellowstone National Park known for its wildlife-rich meadows and excellent trout fishing.

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_69f224b3a7ec819096939414d103e31e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6904138088190ad4209ce7caa4ea3 completed May 3, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d0ace6f6c8190a8d3448a5abfc95a completed Aug. 13, 2026, 12:07 a.m.
NEDg Description generation batch_6a7d0b5dfc388190a160923af44c5319 completed Aug. 13, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a7d0bc73c9c8190ae0a9cd867697207 completed Aug. 13, 2026, 12:11 a.m.
Created at: April 29, 2026, 8:43 p.m.