Triple

T36582222
Position Surface form Disambiguated ID Type / Status
Subject Lansford, Pennsylvania E902425 entity
Predicate hasAttraction P105 FINISHED
Object No. 9 Coal Mine and Museum
The No. 9 Coal Mine and Museum is a historic anthracite coal mine in Lansford, Pennsylvania, now operating as a museum that offers underground tours and exhibits on coal mining history and local heritage.
E2190698 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: No. 9 Coal Mine and Museum | Statement: [Lansford, Pennsylvania, hasAttraction, No. 9 Coal Mine and Museum]
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: No. 9 Coal Mine and Museum
Triple: [Lansford, Pennsylvania, hasAttraction, No. 9 Coal Mine and Museum]
Generated description
The No. 9 Coal Mine and Museum is a historic anthracite coal mine in Lansford, Pennsylvania, now operating as a museum that offers underground tours and exhibits on coal mining history and local heritage.

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_69f76e64d8908190868473959a250b94 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c2cfcfd481909ab9431988d5a8a9 completed May 3, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39f916a9c881909388b5b43e22d5d3 completed June 23, 2026, 3:10 a.m.
NEDg Description generation batch_6a39faecc73c8190876eeb650e791160 completed June 23, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a39fcda8cf481908862a0458439039a completed June 23, 2026, 3:26 a.m.
Created at: May 3, 2026, 4:11 p.m.