Triple

T37119028
Position Surface form Disambiguated ID Type / Status
Subject Paint Branch E919196 entity
Predicate hasTributary P415 FINISHED
Object Little Paint Branch
Little Paint Branch is a small stream in Maryland that serves as a tributary within the Paint Branch watershed, contributing to the Anacostia River system.
 E2213436 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: Little Paint Branch | Statement: [Paint Branch, hasTributary, Little Paint Branch]
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: Little Paint Branch
Triple: [Paint Branch, hasTributary, Little Paint Branch]
Generated description
Little Paint Branch is a small stream in Maryland that serves as a tributary within the Paint Branch watershed, contributing to the Anacostia River system.

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_69f76e9c57148190ba789dd059645bb9 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb30186cf4819095527689754e3c6e completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f6a198990819085ac8c903b6936e0 completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6b00a9788190b91e5ef4c2af8340 completed June 27, 2026, 6:17 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6b8877dc8190869db81917018452 completed June 27, 2026, 6:19 a.m.
Created at: May 3, 2026, 4:15 p.m.