Triple

T34735024
Position Surface form Disambiguated ID Type / Status
Subject Interstate 210 E1001314 entity
Predicate passesThrough P225 FINISHED
Object Fontana
Fontana is a city in San Bernardino County, California, known as a major logistics and transportation hub in the Inland Empire.
E1923415 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: Fontana | Statement: [Interstate 210, passesThrough, Fontana]
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: Fontana
Triple: [Interstate 210, passesThrough, Fontana]
Generated description
Fontana is a city in San Bernardino County, California, known as a major logistics and transportation hub in the Inland Empire.

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_69f76daf739881909ed3554f98a2b433 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779cb00188190bd644ca020b28de7 completed May 3, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3766286c8c8190ac3f5ed56aa065e5 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a3767e5df888190b19eb6b966f91c28 completed June 21, 2026, 4:26 a.m.
NED2 Entity disambiguation (via description) batch_6a3768467d608190b0287a796546281f completed June 21, 2026, 4:27 a.m.
Created at: May 3, 2026, 3:59 p.m.