Triple

T15807502
Position Surface form Disambiguated ID Type / Status
Subject Washington State Route 17 E383255 entity
Predicate connectsTo P845 FINISHED
Object State Route 171
State Route 171 is a short state highway in Washington that serves as a connector route between the town of Warden and the larger regional highway network.
 E1851136 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 171 | Statement: [Washington State Route 17, connectsTo, State Route 171]
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 171
Triple: [Washington State Route 17, connectsTo, State Route 171]
Generated description
State Route 171 is a short state highway in Washington that serves as a connector route between the town of Warden and the larger regional highway network.

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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b52751348190964e82463ce9dd20 completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a25377b44bc81909ec4c1952d8cfad0 completed June 7, 2026, 9:18 a.m.
NEDg Description generation batch_6a253bdcaf2c8190b24d33e76d6efc78 completed June 7, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_6a253fd1f0488190abea40d50e953b04 completed June 7, 2026, 9:54 a.m.
Created at: April 10, 2026, 4:48 a.m.