Triple

T27248329
Position Surface form Disambiguated ID Type / Status
Subject Missouri Route 266 E687411 entity
Predicate isNumberedBefore P11124 FINISHED
Object Missouri Route 267
Missouri Route 267 is a short state highway in the St. Louis, Missouri area that serves local traffic between suburban communities and major connecting routes.
E1812501 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: Missouri Route 267 | Statement: [Missouri Route 266, isNumberedBefore, Missouri Route 267]
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: Missouri Route 267
Triple: [Missouri Route 266, isNumberedBefore, Missouri Route 267]
Generated description
Missouri Route 267 is a short state highway in the St. Louis, Missouri area that serves local traffic between suburban communities and major connecting routes.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626b3e5508190acb0c7b03e465b31 completed May 2, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606e918588190ac8ab005b6f87e58 completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a161404f5908190993589611f152cd1 completed May 26, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a1616734eac8190947663ebe6c3d478 completed May 26, 2026, 9:53 p.m.
Created at: April 27, 2026, 10:43 a.m.