Triple

T19600800
Position Surface form Disambiguated ID Type / Status
Subject AL 3 E470468 entity
Predicate hasDesignation P974 FINISHED
Object State Route 3
State Route 3 is a primary north–south state highway in Alabama that largely follows the route of U.S. Highway 31 through the state.
 E2271793 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 3 | Statement: [AL 3, hasDesignation, State Route 3]
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 3
Triple: [AL 3, hasDesignation, State Route 3]
Generated description
State Route 3 is a primary north–south state highway in Alabama that largely follows the route of U.S. Highway 31 through 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6407df98c8190b258ac3b690fe4b1 completed April 20, 2026, 3:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41cc874ae88190bd163e4bcfe569f7 completed June 29, 2026, 1:38 a.m.
NEDg Description generation batch_6a41cdab97bc8190a6fef8d57f05a86e completed June 29, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a41ce4cee4481909d34941327630fb7 completed June 29, 2026, 1:45 a.m.
Created at: April 10, 2026, 1:43 p.m.