Triple
T28571826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive branch of Ohio |
E723131
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Ohio Department of Aging
The Ohio Department of Aging is a state agency that plans, coordinates, and advocates for services and programs supporting older adults and their caregivers across Ohio.
|
E1825782
|
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: Ohio Department of Aging | Statement: [Executive branch of Ohio, hasPart, Ohio Department of Aging]
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: Ohio Department of Aging Triple: [Executive branch of Ohio, hasPart, Ohio Department of Aging]
Generated description
The Ohio Department of Aging is a state agency that plans, coordinates, and advocates for services and programs supporting older adults and their caregivers across Ohio.
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_69f01d7e97708190ae9e77ee66a68abd |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f650930d088190982ac09775d5b177 |
completed | May 2, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1cb6ede350819082b45afbf848a7f3 |
completed | May 31, 2026, 10:32 p.m. |
| NEDg | Description generation | batch_6a1cbadae2b88190923794f499874f0d |
completed | May 31, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1cbb4e3c4081909221f3997a54efb7 |
completed | May 31, 2026, 10:50 p.m. |
Created at: April 28, 2026, 4:10 a.m.