Triple

T30752416
Position Surface form Disambiguated ID Type / Status
Subject Louisiana Highway 17 E782989 entity
Predicate hasJunctionWith P1018 FINISHED
Object Louisiana Highway 134
Louisiana Highway 134 is a state highway in northeastern Louisiana that serves as an east–west connector route linking rural communities and other regional highways.
 E1931662 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: Louisiana Highway 134 | Statement: [Louisiana Highway 17, hasJunctionWith, Louisiana Highway 134]
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: Louisiana Highway 134
Triple: [Louisiana Highway 17, hasJunctionWith, Louisiana Highway 134]
Generated description
Louisiana Highway 134 is a state highway in northeastern Louisiana that serves as an east–west connector route linking rural communities and other regional highways.

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_69f224af8d8481908bea03890c5618be completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68f91f0cc8190936582859f7d1683 completed May 2, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b08e4d708190b7aca0fe893e541f completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b474de208190b602fcb13061ce98 completed June 10, 2026, 12:48 a.m.
NED2 Entity disambiguation (via description) batch_6a28b54c10288190915b789c2f1b250d completed June 10, 2026, 12:52 a.m.
Created at: April 29, 2026, 8:39 p.m.