Triple
T17745224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenda Frese |
E442969
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Frese
Frese is the surname of American college basketball coach Brenda Frese, best known for leading the University of Maryland women's basketball program.
|
E1284689
|
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: Frese | Statement: [Brenda Frese, familyName, Frese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frese Context triple: [Brenda Frese, familyName, Frese]
-
A.
Fressenda
Fressenda was an 11th-century Norman noblewoman of the Hauteville family, notable as the wife of Tancred of Hauteville and a matriarch of the Norman rulers in southern Italy and Sicily.
-
B.
Freirina
Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
-
C.
Freser
Freser is a river in Catalonia, Spain, known for flowing through the Pyrenees and joining the Ter River.
-
D.
Frusino
Frusino was an ancient town of central Italy in the region of Samnium, known from Roman-era administrative geography.
-
E.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
- 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: Frese Triple: [Brenda Frese, familyName, Frese]
Generated description
Frese is the surname of American college basketball coach Brenda Frese, best known for leading the University of Maryland women's basketball program.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frese Target entity description: Frese is the surname of American college basketball coach Brenda Frese, best known for leading the University of Maryland women's basketball program.
-
A.
Fressenda
Fressenda was an 11th-century Norman noblewoman of the Hauteville family, notable as the wife of Tancred of Hauteville and a matriarch of the Norman rulers in southern Italy and Sicily.
-
B.
Freirina
Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
-
C.
Freser
Freser is a river in Catalonia, Spain, known for flowing through the Pyrenees and joining the Ter River.
-
D.
Frusino
Frusino was an ancient town of central Italy in the region of Samnium, known from Roman-era administrative geography.
-
E.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad0c5b481909059bfa868cc4001 |
completed | April 19, 2026, 6:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a024300b5048190ba50198a7637441d |
completed | May 11, 2026, 8:58 p.m. |
| NEDg | Description generation | batch_6a02449a76d8819099e72cd53f908255 |
completed | May 11, 2026, 9:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a024530b5dc8190a4776863cc01babf |
completed | May 11, 2026, 9:08 p.m. |
Created at: April 10, 2026, 10:09 a.m.