Triple
T13712327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Lilly Poetry Prize |
E328803
|
entity |
| Predicate | hasRecipient |
P108
|
FINISHED |
| Object | Donald Hall |
E346100
|
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: Donald Hall | Statement: [Ruth Lilly Poetry Prize, hasRecipient, Donald Hall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Hall Context triple: [Ruth Lilly Poetry Prize, hasRecipient, Donald Hall]
-
A.
Donald Hall
chosen
Donald Hall was a prominent American poet, essayist, and former U.S. Poet Laureate known for his reflective, rural-themed verse and influential contributions to contemporary poetry.
-
B.
John Kooser
John Kooser was an individual significant enough in local or regional history that a Pennsylvania state park was named in his honor.
-
C.
A. R. Ammons
A. R. Ammons was an influential 20th-century American poet known for his meditative, nature-focused verse and innovative long-form poems.
-
D.
Stephen Dunn
Stephen Dunn was an American poet and Pulitzer Prize winner known for his accessible, reflective verse exploring everyday life and human relationships.
-
E.
Doug Mahon
Doug Mahon is a technology entrepreneur best known as a founder of the data storage company Seagate Technology.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd4395e8c0819098719c8cd344aa33 |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a845a29c81908096a785f5af5521 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:54 p.m.