Triple

T19571562
Position Surface form Disambiguated ID Type / Status
Subject La Crosse, Washington E489728 entity
Predicate roadAccess P385 FINISHED
Object State Route 127
State Route 127 is a state highway in Washington that serves as a key rural connector in the southeastern part of the state.
 E2267901 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 127 | Statement: [La Crosse, Washington, roadAccess, State Route 127]
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 127
Triple: [La Crosse, Washington, roadAccess, State Route 127]
Generated description
State Route 127 is a state highway in Washington that serves as a key rural connector in the southeastern part of the state.

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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6402103208190b80acdfa82b7a9c4 completed April 20, 2026, 3:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b27cfcb88190b700f5be4db760d2 completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b361ef3c8190beaed54507ba59d5 completed June 28, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_6a41b4ab67288190bf774036d4fe05e2 completed June 28, 2026, 11:56 p.m.
Created at: April 10, 2026, 1:42 p.m.