Triple

T23484379
Position Surface form Disambiguated ID Type / Status
Subject Seaford, Delaware E570492 entity
Predicate hasTransportation P105 FINISHED
Object Delaware Route 13A
Delaware Route 13A is a state highway in Sussex County, Delaware, serving as an alternate route of U.S. Route 13 that passes through the city of Seaford.
E1610457 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: Delaware Route 13A | Statement: [Seaford, Delaware, hasTransportation, Delaware Route 13A]
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: Delaware Route 13A
Triple: [Seaford, Delaware, hasTransportation, Delaware Route 13A]
Generated description
Delaware Route 13A is a state highway in Sussex County, Delaware, serving as an alternate route of U.S. Route 13 that passes through the city of Seaford.

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_69e245b0b01481908f636939bedd804c completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a752c678819087e5c50b8cf87d3d completed April 29, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75ed2b288190a0308290784ae994 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77855e2c81909c3e92f499d134dc completed May 21, 2026, 9:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0f790a4d648190b210725d44601bca completed May 21, 2026, 9:28 p.m.
Created at: April 17, 2026, 6:03 p.m.