Triple

T16093340
Position Surface form Disambiguated ID Type / Status
Subject Texas state highways E390416 entity
Predicate hasComponent P35 FINISHED
Object State Highway 17
State Highway 17 is a Texas state highway that runs through the Trans-Pecos region, connecting the city of Marfa to Pecos and serving as a scenic route in far West Texas.
 E2223235 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 17 | Statement: [Texas state highways, hasComponent, State Highway 17]
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 17
Triple: [Texas state highways, hasComponent, State Highway 17]
Generated description
State Highway 17 is a Texas state highway that runs through the Trans-Pecos region, connecting the city of Marfa to Pecos and serving as a scenic route in far West Texas.

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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858ed09881909bde122971d95753 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a406cb47048819096c51142ec6deee5 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406db565b881909769124848e2b508 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
Created at: April 10, 2026, 4:59 a.m.