Triple

T24250938
Position Surface form Disambiguated ID Type / Status
Subject Gough Street E603521 entity
Predicate hasIntersectingStreet P72012 FINISHED
Object Union Street
Union Street is a major east–west thoroughfare in San Francisco, California, known for its shops, restaurants, and historic architecture.
 E81267 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: Union Street | Statement: [Gough Street, hasIntersectingStreet, Union 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: Union Street
Triple: [Gough Street, hasIntersectingStreet, Union Street]
Generated description
Union Street is a major east–west thoroughfare in San Francisco, California, known for its shops, restaurants, and historic architecture.

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_69e29540da0481909a38bdae315b7a02 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28b89eb8081909ccf37081add5cee completed April 29, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e5737fd408190812eda47191c7587 completed June 26, 2026, 10:40 a.m.
NEDg Description generation batch_6a3e591d57608190bd82a60c74d1ae1d completed June 26, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a3e5f4a910081908f9ff844c1feb1ae completed June 26, 2026, 11:15 a.m.
Created at: April 18, 2026, 12:04 a.m.