Triple

T28686531
Position Surface form Disambiguated ID Type / Status
Subject Monroe, Washington E729148 entity
Predicate hasHistoricArea P5057 FINISHED
Object downtown Monroe historic district
The downtown Monroe historic district is a preserved area in Monroe, Washington, known for its early 20th-century commercial architecture and its role as the historic core of the city.
E1828487 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: downtown Monroe historic district | Statement: [Monroe, Washington, hasHistoricArea, downtown Monroe historic district]
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: downtown Monroe historic district
Triple: [Monroe, Washington, hasHistoricArea, downtown Monroe historic district]
Generated description
The downtown Monroe historic district is a preserved area in Monroe, Washington, known for its early 20th-century commercial architecture and its role as the historic core of the city.

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_69f043e60b6c8190ac2cd042e77fe6e9 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65681703481909721d858830afd86 completed May 2, 2026, 7:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc3ae3a1c81909173bf48566b36e3 completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc473fd3081909541a90b275216bf completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc5027a4881908055cfa03af83b64 completed May 31, 2026, 11:32 p.m.
Created at: April 28, 2026, 5:32 a.m.