Triple

T30696518
Position Surface form Disambiguated ID Type / Status
Subject Gorman, Maryland E781482 entity
Predicate hasTransportation P105 FINISHED
Object Maryland Route 560
Maryland Route 560 is a state highway in western Maryland that connects the community of Gorman to nearby towns through the rural, mountainous terrain of Garrett County.
E2104642 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: Maryland Route 560 | Statement: [Gorman, Maryland, hasTransportation, Maryland Route 560]
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: Maryland Route 560
Triple: [Gorman, Maryland, hasTransportation, Maryland Route 560]
Generated description
Maryland Route 560 is a state highway in western Maryland that connects the community of Gorman to nearby towns through the rural, mountainous terrain of Garrett County.

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_69f224ab24e08190991d6edb6df58e8b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68bdb794081908300432bee61bcf6 completed May 2, 2026, 11:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3740e62798819080a04afa3929b1a9 completed June 21, 2026, 1:39 a.m.
NEDg Description generation batch_6a3742189084819080ee9c2cb39751a1 completed June 21, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a374329be488190bffd50363cf3b8f0 completed June 21, 2026, 1:49 a.m.
Created at: April 29, 2026, 8:34 p.m.