Triple
T38442673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bell County, Kentucky |
E906540
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Joshua Fry Bell
Joshua Fry Bell was a 19th-century American lawyer and politician from Kentucky who served in the U.S. House of Representatives and as Kentucky’s Secretary of State.
|
E2269582
|
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: Joshua Fry Bell | Statement: [Bell County, Kentucky, namedAfter, Joshua Fry Bell]
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: Joshua Fry Bell Triple: [Bell County, Kentucky, namedAfter, Joshua Fry Bell]
Generated description
Joshua Fry Bell was a 19th-century American lawyer and politician from Kentucky who served in the U.S. House of Representatives and as Kentucky’s Secretary of State.
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_69f76e72878c8190a692836c8b01b58b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fccdd734e08190b67e48ac872cc18c |
completed | May 7, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41c29ba5f881909557b9d5d3f86b6e |
completed | June 29, 2026, 12:55 a.m. |
| NEDg | Description generation | batch_6a41c3dac6ec81909231576db0b9808d |
completed | June 29, 2026, 1:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41c481f72c8190b44745166b1bb8c4 |
completed | June 29, 2026, 1:04 a.m. |
Created at: May 3, 2026, 4:31 p.m.