Triple

T26511464
Position Surface form Disambiguated ID Type / Status
Subject Downtown San Bernardino E669693 entity
Predicate traversedBy P225 FINISHED
Object E Street
E Street is a major north–south thoroughfare in San Bernardino, California, serving as a key commercial and transit corridor through the city’s downtown.
 E1727283 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: E Street | Statement: [Downtown San Bernardino, traversedBy, E 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: E Street
Triple: [Downtown San Bernardino, traversedBy, E Street]
Generated description
E Street is a major north–south thoroughfare in San Bernardino, California, serving as a key commercial and transit corridor through the city’s downtown.

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_69eeb319ec70819090834c2591cf5f1e completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61392ec5081909382ace560650d77 completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb3be0708190b4b3b57153361141 completed May 23, 2026, 2:35 p.m.
NEDg Description generation batch_6a11be61ba0c8190b932a96eda11e624 completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bf2f222c8190ae2e6bcb73204856 completed May 23, 2026, 2:52 p.m.
Created at: April 27, 2026, 1:20 a.m.