Triple

T30057564
Position Surface form Disambiguated ID Type / Status
Subject RTA E763773 entity
Predicate operatesIn P82 FINISHED
Object Jefferson Parish (limited services)
Jefferson Parish (limited services) is a suburban parish in the Greater New Orleans area of Louisiana that receives only partial transit coverage from the city’s Regional Transit Authority.
E1895841 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: Jefferson Parish (limited services) | Statement: [RTA, operatesIn, Jefferson Parish (limited services)]
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: Jefferson Parish (limited services)
Triple: [RTA, operatesIn, Jefferson Parish (limited services)]
Generated description
Jefferson Parish (limited services) is a suburban parish in the Greater New Orleans area of Louisiana that receives only partial transit coverage from the city’s Regional Transit Authority.

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_69f224716378819087a722e487832b70 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67c9fe7b48190b79b4041357edb49 completed May 2, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27324919ec819088a6e590361a703b completed June 8, 2026, 9:21 p.m.
NEDg Description generation batch_6a273328906c8190b9a0ebac5f8aa128 completed June 8, 2026, 9:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2733bc41f88190a21dcfb4f8f492d3 completed June 8, 2026, 9:27 p.m.
Created at: April 29, 2026, 6:56 p.m.