Triple

T17163107
Position Surface form Disambiguated ID Type / Status
Subject Freestone County, Texas E416530 entity
Predicate hasMajorHighway P385 FINISHED
Object State Highway 75
State Highway 75 is a north–south state highway in Texas that largely follows the route of the former U.S. Highway 75, connecting several communities between the Houston and Dallas regions.
E2285031 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 Highway 75 | Statement: [Freestone County, Texas, hasMajorHighway, State Highway 75]
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 Highway 75
Triple: [Freestone County, Texas, hasMajorHighway, State Highway 75]
Generated description
State Highway 75 is a north–south state highway in Texas that largely follows the route of the former U.S. Highway 75, connecting several communities between the Houston and Dallas regions.

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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f91316108190b0d856d6fa5cd509 completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a44be059880819090fdf39a82d8f90b completed July 1, 2026, 7:13 a.m.
NEDg Description generation batch_6a44bf20f9a08190ab38324fc824835c completed July 1, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_6a44c00a843081908e61d70a3de28a75 completed July 1, 2026, 7:21 a.m.
Created at: April 10, 2026, 5:37 a.m.