Triple
T13954389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Farley |
E335615
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object |
Thomas Farley
Thomas Farley was the father of American comedian and actor Chris Farley, known primarily in public references for this familial connection.
|
E1075974
|
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: Thomas Farley | Statement: [Chris Farley, parent, Thomas Farley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Farley Context triple: [Chris Farley, parent, Thomas Farley]
-
A.
George L. Kelling
George L. Kelling was an American criminologist best known for co-developing the "broken windows" theory of policing and urban disorder.
-
B.
Thomas M. Milano
Thomas M. Milano is the father of American actress and activist Alyssa Milano.
-
C.
John Foley
John Foley is a common name shared by several notable individuals, including a Jesuit priest and hymn composer, a former Peloton CEO, and various athletes and public figures.
-
D.
Thomas Phifer
Thomas Phifer is an American architect known for his minimalist, light-filled designs that harmonize contemporary architecture with natural landscapes.
-
E.
James Follett
James Follett is a British author and screenwriter known for his science fiction novels and radio dramas, as well as his work on film and television scripts.
- 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: Thomas Farley Triple: [Chris Farley, parent, Thomas Farley]
Generated description
Thomas Farley was the father of American comedian and actor Chris Farley, known primarily in public references for this familial connection.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Farley Target entity description: Thomas Farley was the father of American comedian and actor Chris Farley, known primarily in public references for this familial connection.
-
A.
George L. Kelling
George L. Kelling was an American criminologist best known for co-developing the "broken windows" theory of policing and urban disorder.
-
B.
Thomas M. Milano
Thomas M. Milano is the father of American actress and activist Alyssa Milano.
-
C.
John Foley
John Foley is a common name shared by several notable individuals, including a Jesuit priest and hymn composer, a former Peloton CEO, and various athletes and public figures.
-
D.
Thomas Phifer
Thomas Phifer is an American architect known for his minimalist, light-filled designs that harmonize contemporary architecture with natural landscapes.
-
E.
James Follett
James Follett is a British author and screenwriter known for his science fiction novels and radio dramas, as well as his work on film and television scripts.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e78a4a481908e438745631a43c0 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc321c600819085052392de9b0b53 |
completed | May 6, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69fc26cfe8588190a7204dd9b966d26d |
completed | May 7, 2026, 5:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fc27d1aaa08190a00cb15e5beb8c88 |
completed | May 7, 2026, 5:49 a.m. |
Created at: April 9, 2026, 10:17 p.m.