Triple
T10243380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kooser State Park |
E243654
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
John Kooser
John Kooser was an individual significant enough in local or regional history that a Pennsylvania state park was named in his honor.
|
E853527
|
NE FINISHED |
How this triple was built (4 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: John Kooser | Statement: [Kooser State Park, namedAfter, John Kooser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Kooser Context triple: [Kooser State Park, namedAfter, John Kooser]
-
A.
Ted Kooser
Ted Kooser is an American poet, essayist, and former U.S. Poet Laureate known for his accessible, plainspoken verse about Midwestern life.
-
B.
Donald Hall
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.
-
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.
Doug Mahon
Doug Mahon is a technology entrepreneur best known as a founder of the data storage company Seagate Technology.
-
E.
Stephen Dunn
Stephen Dunn was an American poet and Pulitzer Prize winner known for his accessible, reflective verse exploring everyday life and human relationships.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: John Kooser Triple: [Kooser State Park, namedAfter, John Kooser]
Generated description
John Kooser was an individual significant enough in local or regional history that a Pennsylvania state park was named in his honor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Kooser Target entity description: John Kooser was an individual significant enough in local or regional history that a Pennsylvania state park was named in his honor.
-
A.
Ted Kooser
Ted Kooser is an American poet, essayist, and former U.S. Poet Laureate known for his accessible, plainspoken verse about Midwestern life.
-
B.
Donald Hall
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.
-
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.
Doug Mahon
Doug Mahon is a technology entrepreneur best known as a founder of the data storage company Seagate Technology.
-
E.
Stephen Dunn
Stephen Dunn was an American poet and Pulitzer Prize winner known for his accessible, reflective verse exploring everyday life and human relationships.
- F. None of above. chosen
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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22a76188190a73df23bfb08eb3d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7936ce4819087f07df2c7a76282 |
completed | April 9, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69d6fa2f7a848190a9de5de4d0f3f110 |
completed | April 9, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fcbab3ec8190ade1c0223c22ad58 |
completed | April 9, 2026, 1:11 a.m. |
Created at: April 6, 2026, 11:25 a.m.