Triple

T27396541
Position Surface form Disambiguated ID Type / Status
Subject Olympic Boulevard E691702 entity
Predicate hasIntersectionWith P13379 FINISHED
Object Hoover Street
Hoover Street is a major north–south thoroughfare in Los Angeles, California, running through several central neighborhoods and connecting with key east–west arteries.
E2286136 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: Hoover Street | Statement: [Olympic Boulevard, hasIntersectionWith, Hoover Street]
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: Hoover Street
Triple: [Olympic Boulevard, hasIntersectionWith, Hoover Street]
Generated description
Hoover Street is a major north–south thoroughfare in Los Angeles, California, running through several central neighborhoods and connecting with key east–west arteries.

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_69ef5204f7048190bf226a129858fc5b completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cb0a760819081645b11597dc502 completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a464f1c36288190a0d6373f6b3bff4a completed July 2, 2026, 11:44 a.m.
NEDg Description generation batch_6a464feae5a08190ab244199838161ec completed July 2, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_6a4650f219788190945e7fdafd043cc9 completed July 2, 2026, 11:52 a.m.
Created at: April 27, 2026, 12:27 p.m.