Triple

T24096360
Position Surface form Disambiguated ID Type / Status
Subject New Harmony, Indiana E596929 entity
Predicate hasLandmark P105 FINISHED
Object Workingmen’s Institute
The Workingmen’s Institute is a historic library and museum in New Harmony, Indiana, founded in the 19th century to promote education and self-improvement among workers.
E1616283 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: Workingmen’s Institute | Statement: [New Harmony, Indiana, hasLandmark, Workingmen’s Institute]
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: Workingmen’s Institute
Triple: [New Harmony, Indiana, hasLandmark, Workingmen’s Institute]
Generated description
The Workingmen’s Institute is a historic library and museum in New Harmony, Indiana, founded in the 19th century to promote education and self-improvement among workers.

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_69e288c548048190a5c1018da1166a21 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dd265274819094f7f29bd8c1c071 completed April 29, 2026, 10:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f967c8eec819082aa2c9a8cbdfc8e completed May 21, 2026, 11:34 p.m.
NEDg Description generation batch_6a0f974fb2e08190a535a92ead622159 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9817d9248190aa2f7cc8fc2916bf completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 10:59 p.m.