Triple

T24601697
Position Surface form Disambiguated ID Type / Status
Subject Marksville, Louisiana E608842 entity
Predicate hasMajorHighway P385 FINISHED
Object Louisiana Highway 107
Louisiana Highway 107 is a state highway in central Louisiana that connects several communities, including Marksville, and serves as a regional route for local and through traffic.
E1685243 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 107 | Statement: [Marksville, Louisiana, hasMajorHighway, Louisiana Highway 107]
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 107
Triple: [Marksville, Louisiana, hasMajorHighway, Louisiana Highway 107]
Generated description
Louisiana Highway 107 is a state highway in central Louisiana that connects several communities, including Marksville, and serves as a regional route for local and through traffic.

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_69e2c4d060e08190ac9f7c49b1036e20 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2aa2b980081909abd09a5906db7e4 completed April 30, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad26d9708190837e274390a9a54a completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10ae0e67c0819087189306e39cdbc7 completed May 22, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_6a10ae851d548190a19c0f9293b99e24 completed May 22, 2026, 7:29 p.m.
Created at: April 18, 2026, 2:30 a.m.