Triple
T8562569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Pedro Colley |
E202723
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Colley
Colley is a surname most notably associated with American actor Don Pedro Colley, known for his roles in film and television during the 1960s–1980s.
|
E744059
|
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: Colley | Statement: [Don Pedro Colley, familyName, Colley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colley Context triple: [Don Pedro Colley, familyName, Colley]
-
A.
Anson’s Colts
Anson’s Colts was an early Major League Baseball team from Chicago in the late 19th century, managed and led by Hall of Famer Cap Anson.
-
B.
McCauley
McCauley is the maiden surname of Rosa Parks, the prominent American civil rights activist known for her pivotal role in the Montgomery bus boycott.
-
C.
Collett
Collett is the surname of Australian actress and producer Toni Collette, known for her versatile performances in film, television, and theatre.
-
D.
Leahey
Leahey is a surname variant of Leahy, an Irish family name of Gaelic origin.
-
E.
Hackett
Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
- 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: Colley Triple: [Don Pedro Colley, familyName, Colley]
Generated description
Colley is a surname most notably associated with American actor Don Pedro Colley, known for his roles in film and television during the 1960s–1980s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Colley Target entity description: Colley is a surname most notably associated with American actor Don Pedro Colley, known for his roles in film and television during the 1960s–1980s.
-
A.
Anson’s Colts
Anson’s Colts was an early Major League Baseball team from Chicago in the late 19th century, managed and led by Hall of Famer Cap Anson.
-
B.
McCauley
McCauley is the maiden surname of Rosa Parks, the prominent American civil rights activist known for her pivotal role in the Montgomery bus boycott.
-
C.
Collett
Collett is the surname of Australian actress and producer Toni Collette, known for her versatile performances in film, television, and theatre.
-
D.
Leahey
Leahey is a surname variant of Leahy, an Irish family name of Gaelic origin.
-
E.
Hackett
Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe94c0c3c8190aca981c07b090dc0 |
completed | March 31, 2026, 3:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce895657188190886779180b783bf3 |
completed | April 2, 2026, 3:20 p.m. |
| NEDg | Description generation | batch_69ce8a9ce1a08190a579f7f7a0319d01 |
completed | April 2, 2026, 3:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce8bdf1f148190ac832424661bd8e5 |
completed | April 2, 2026, 3:31 p.m. |
Created at: March 30, 2026, 6:20 p.m.