Triple
T12329907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Perry |
E293931
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Perry
Perry is a common English surname borne by numerous notable individuals across sports, entertainment, politics, and other fields.
|
E60656
|
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: Perry | Statement: [Fred Perry, familyName, Perry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perry Context triple: [Fred Perry, familyName, Perry]
-
A.
Perry
Perry is the central character in the film "Makers," around whom the story’s main events and themes revolve.
-
B.
Perry
Perry is a small rural town located in Dane County, Wisconsin, known for its agricultural landscape and quiet residential character.
-
C.
Perry
Perry is a small village and civil parish in Cambridgeshire, England, situated near Kimbolton and close to Grafham Water.
-
D.
Perry
Perry is a small city in central Georgia known as the county seat of Houston County and for hosting the Georgia National Fair at the Georgia National Fairgrounds and Agricenter.
-
E.
Perry
Perry is a small city in central Iowa known historically as a railroad and agricultural community.
- 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: Perry Triple: [Fred Perry, familyName, Perry]
Generated description
Perry is a common English surname borne by numerous notable individuals across sports, entertainment, politics, and other fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Perry Target entity description: Perry is a common English surname borne by numerous notable individuals across sports, entertainment, politics, and other fields.
-
A.
Perry
chosen
Perry is a common English surname borne by numerous notable individuals across politics, arts, sports, and other fields.
-
B.
Perry
Perry is a fictional character played by British comedian and actress Katherine Lucy Bridget Burke, best known for her work in television comedy.
-
C.
Perry
Perry is one of the two socially awkward teenage protagonists in the British comedy film "Kevin & Perry Go Large," known for his obsession with clubbing, DJ culture, and losing his virginity.
-
D.
Perry
Perry is the central character in the film "Makers," around whom the story’s main events and themes revolve.
-
E.
Perry
Perry is a small city in northern Utah, United States, known for its rural character and proximity to the Wasatch Mountains and Great Salt Lake.
- F. None of above.
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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6555e525c8190aa72da362fae1e3e |
completed | May 2, 2026, 7:49 p.m. |
| NEDg | Description generation | batch_69f6566dccc0819085e059c7b0288f6c |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f657aec8fc8190b3b08ccb95595958 |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:53 p.m.