Triple

T27556816
Position Surface form Disambiguated ID Type / Status
Subject Third Avenue–149th Street station E695658 entity
Predicate hasConnection P8776 FINISHED
Object Bx2 bus
The Bx2 bus is a New York City Transit route in the Bronx that primarily runs along the Grand Concourse, connecting key commercial and transit hubs.
 E1777846 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: Bx2 bus | Statement: [Third Avenue–149th Street station, hasConnection, Bx2 bus]
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: Bx2 bus
Triple: [Third Avenue–149th Street station, hasConnection, Bx2 bus]
Generated description
The Bx2 bus is a New York City Transit route in the Bronx that primarily runs along the Grand Concourse, connecting key commercial and transit hubs.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62fb4f9688190a3ce7a1580436e35 completed May 2, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5ca5dac819096bf2139fc1094b7 completed May 24, 2026, 9:32 a.m.
NEDg Description generation batch_6a12c73af6348190aa55c00fcaf1d46c completed May 24, 2026, 9:39 a.m.
NED2 Entity disambiguation (via description) batch_6a12c7d1f8e8819093ef8b94c1ec2816 completed May 24, 2026, 9:41 a.m.
Created at: April 27, 2026, 1:37 p.m.