Triple

T18346536
Position Surface form Disambiguated ID Type / Status
Subject City of Redding, California E439553 entity
Predicate servedByHighway P385 FINISHED
Object State Route 273
State Route 273 is a California state highway in Shasta County that functions as a business loop and former alignment of Interstate 5 through the Redding area.
 E2167654 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: State Route 273 | Statement: [City of Redding, California, servedByHighway, State Route 273]
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: State Route 273
Triple: [City of Redding, California, servedByHighway, State Route 273]
Generated description
State Route 273 is a California state highway in Shasta County that functions as a business loop and former alignment of Interstate 5 through the Redding area.

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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f4740c8190b70ba48a4232953e completed April 19, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d5171bec8190bf434fbb9f9ad83c completed June 22, 2026, 6:24 a.m.
NEDg Description generation batch_6a38d60d968081908071371e5bbc1314 completed June 22, 2026, 6:28 a.m.
NED2 Entity disambiguation (via description) batch_6a38d6b7722c81909093057618f2569a completed June 22, 2026, 6:31 a.m.
Created at: April 10, 2026, 10:37 a.m.