Triple

T15127209
Position Surface form Disambiguated ID Type / Status
Subject Ohio State Route 151 E361321 entity
Predicate abbreviation P43 FINISHED
Object State Route 151
State Route 151 is a state highway in eastern Ohio that runs generally east–west, connecting small communities and serving as a regional connector route.
 E1760632 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 151 | Statement: [Ohio State Route 151, abbreviation, State Route 151]
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 151
Triple: [Ohio State Route 151, abbreviation, State Route 151]
Generated description
State Route 151 is a state highway in eastern Ohio that runs generally east–west, connecting small communities and serving as a regional connector route.

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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005a1b9288190954f2d92549805e5 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12534b67048190b4c5d5021bbd26fa completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a1255b908b48190bd81bc6a3526ec09 completed May 24, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12562dd26c8190841d74d2c0d81ac8 completed May 24, 2026, 1:36 a.m.
Created at: April 10, 2026, 3:06 a.m.