Triple

T20242698
Position Surface form Disambiguated ID Type / Status
Subject North Richland Hills/Smithfield station E498337 entity
Predicate near P350 FINISHED
Object Smithfield Road
Smithfield Road is a local thoroughfare in North Richland Hills, Texas, notable for its proximity to the North Richland Hills/Smithfield commuter rail station.
E2095068 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: Smithfield Road | Statement: [North Richland Hills/Smithfield station, near, Smithfield Road]
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: Smithfield Road
Triple: [North Richland Hills/Smithfield station, near, Smithfield Road]
Generated description
Smithfield Road is a local thoroughfare in North Richland Hills, Texas, notable for its proximity to the North Richland Hills/Smithfield commuter rail station.

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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6716f9d248190a145f6883827ebbe completed April 20, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a370d9c5cbc8190b723225870d53430 completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e0b0aa48190b90fc81dcae939a3 completed June 20, 2026, 10:02 p.m.
NED2 Entity disambiguation (via description) batch_6a370e86b49c819095d85125ac8a3780 completed June 20, 2026, 10:04 p.m.
Created at: April 11, 2026, 11:40 p.m.