Triple

T16093333
Position Surface form Disambiguated ID Type / Status
Subject Texas state highways E390416 entity
Predicate hasComponent P35 FINISHED
Object State Highway 249
State Highway 249 is a major Texas roadway in the Houston metropolitan area, serving as a key northwestern corridor connecting suburban communities and facilitating regional traffic flow.
 E2214164 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 249 | Statement: [Texas state highways, hasComponent, State Highway 249]
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 249
Triple: [Texas state highways, hasComponent, State Highway 249]
Generated description
State Highway 249 is a major Texas roadway in the Houston metropolitan area, serving as a key northwestern corridor connecting suburban communities and facilitating regional traffic flow.

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_6a3f69ec53f081908adfc852c6e359b0 completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6c27d8888190a8c2fe4ffc9c94c2 completed June 27, 2026, 6:22 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6c9567fc81909efbb64ae57be131 completed June 27, 2026, 6:24 a.m.
Created at: April 10, 2026, 4:59 a.m.