Triple

T38513469
Position Surface form Disambiguated ID Type / Status
Subject 4th Street NW and D Street NW E921975 entity
Predicate hasStreet P959 FINISHED
Object 4th Street NW
4th Street NW is a major north–south thoroughfare in Washington, D.C.’s Northwest quadrant, running through the city’s downtown and adjacent neighborhoods.
E2277462 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: 4th Street NW | Statement: [4th Street NW and D Street NW, hasStreet, 4th Street NW]
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: 4th Street NW
Triple: [4th Street NW and D Street NW, hasStreet, 4th Street NW]
Generated description
4th Street NW is a major north–south thoroughfare in Washington, D.C.’s Northwest quadrant, running through the city’s downtown and adjacent neighborhoods.

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_69f76ea3c5448190aa7002fc1ba3f874 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd28e4d68819083ea0fa4a731fa43 completed May 7, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ea843ea481908644f2986d823df7 completed June 29, 2026, 3:46 a.m.
NEDg Description generation batch_6a41ebcc57788190b0480326b2904b79 completed June 29, 2026, 3:51 a.m.
NED2 Entity disambiguation (via description) batch_6a41ef7de8c08190948d909b8e5edbc1 completed June 29, 2026, 4:07 a.m.
Created at: May 3, 2026, 4:32 p.m.