Triple

T32389957
Position Surface form Disambiguated ID Type / Status
Subject Point Loma (neighborhood) E827641 entity
Predicate transportServedBy P1298 FINISHED
Object Nimitz Boulevard
Nimitz Boulevard is a major thoroughfare in San Diego, California, providing a key connection between the Point Loma peninsula and the rest of the city’s roadway network.
E2038187 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: Nimitz Boulevard | Statement: [Point Loma (neighborhood), transportServedBy, Nimitz Boulevard]
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: Nimitz Boulevard
Triple: [Point Loma (neighborhood), transportServedBy, Nimitz Boulevard]
Generated description
Nimitz Boulevard is a major thoroughfare in San Diego, California, providing a key connection between the Point Loma peninsula and the rest of the city’s roadway network.

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_69f349184e7481909c6c54428cb9cf12 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c1d48d048190b6bb79e26881adb7 completed May 3, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3515f5cae48190b708a3f5bd6cd10a completed June 19, 2026, 10:12 a.m.
NEDg Description generation batch_6a3516f0a8748190bb2a2e6bb7c2b7cd completed June 19, 2026, 10:16 a.m.
NED2 Entity disambiguation (via description) batch_6a35191798188190b1738ac2d2e5e2fd completed June 19, 2026, 10:25 a.m.
Created at: May 1, 2026, 12:52 a.m.