Triple

T35669553
Position Surface form Disambiguated ID Type / Status
Subject Interstate 110 in Los Angeles E1030672 entity
Predicate connectsTo P845 FINISHED
Object State Route 213
State Route 213 is a California state highway in the Los Angeles area that primarily follows Western Avenue, linking coastal communities with major freeways and urban neighborhoods.
 E2297645 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 213 | Statement: [Interstate 110 in Los Angeles, connectsTo, State Route 213]
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 213
Triple: [Interstate 110 in Los Angeles, connectsTo, State Route 213]
Generated description
State Route 213 is a California state highway in the Los Angeles area that primarily follows Western Avenue, linking coastal communities with major freeways and urban neighborhoods.

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_69f76e0acfc0819082c8495c2210ce73 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fb10c4881908b12bfceaaf085f1 completed May 3, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a83b9e21f608190ae004ae1d3bb037d completed Aug. 18, 2026, 1:48 a.m.
NEDg Description generation batch_6a83ba499d248190be55e77797923340 completed Aug. 18, 2026, 1:50 a.m.
NED2 Entity disambiguation (via description) batch_6a83baaafcb08190a9f888c906f56150 completed Aug. 18, 2026, 1:51 a.m.
Created at: May 3, 2026, 4:05 p.m.