Triple
T19054115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John J. Eagan |
E466345
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Eagan
Eagan is a surname of Irish origin that is borne by various notable individuals and families.
|
E1367465
|
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: Eagan | Statement: [John J. Eagan, familyName, Eagan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eagan Context triple: [John J. Eagan, familyName, Eagan]
-
A.
Eagan, Minnesota
Eagan, Minnesota is a suburban city in the Minneapolis–Saint Paul metropolitan area known for its major corporate presence and proximity to key regional transportation hubs.
-
B.
Fridley
Fridley is a suburban city in Anoka County, Minnesota, located just north of Minneapolis along the Mississippi River.
-
C.
Minnetonka
Minnetonka is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its residential communities and proximity to Lake Minnetonka.
-
D.
Brainerd
Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
-
E.
Eden Prairie
Eden Prairie is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its residential communities, parks, and corporate offices.
- 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: Eagan Triple: [John J. Eagan, familyName, Eagan]
Generated description
Eagan is a surname of Irish origin that is borne by various notable individuals and families.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eagan Target entity description: Eagan is a surname of Irish origin that is borne by various notable individuals and families.
-
A.
Eagan, Minnesota
Eagan, Minnesota is a suburban city in the Minneapolis–Saint Paul metropolitan area known for its major corporate presence and proximity to key regional transportation hubs.
-
B.
Fridley
Fridley is a suburban city in Anoka County, Minnesota, located just north of Minneapolis along the Mississippi River.
-
C.
Minnetonka
Minnetonka is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its residential communities and proximity to Lake Minnetonka.
-
D.
Brainerd
Brainerd is a small city in central Minnesota, United States, known as a regional hub for outdoor recreation in the lakes area.
-
E.
Eden Prairie
Eden Prairie is a suburban city in the Minneapolis–Saint Paul metropolitan area of Minnesota, known for its residential communities, parks, and corporate offices.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc049f64819093ae9fda26a49bd2 |
completed | April 20, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a070e5964588190957bf7549a074833 |
completed | May 15, 2026, 12:15 p.m. |
| NEDg | Description generation | batch_6a070f2772e881909b3ea02f51c3feb6 |
completed | May 15, 2026, 12:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a070fe766d081909453b1f8563817e8 |
completed | May 15, 2026, 12:21 p.m. |
Created at: April 10, 2026, 12:03 p.m.