Triple
T2666170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Freeman |
E55639
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Joe Freeman
Joe Freeman is the son of English actor Martin Freeman.
|
E293078
|
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: Joe Freeman | Statement: [Martin Freeman, hasChild, Joe Freeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Freeman Context triple: [Martin Freeman, hasChild, Joe Freeman]
-
A.
Max Mullen
Max Mullen is an American entrepreneur best known as a co-founder of the grocery delivery company Instacart.
-
B.
Larry Robinson
Larry Robinson is an American academic and administrator best known for serving as president of Florida A&M University.
-
C.
Larry Robinson
Larry Robinson is a Hall of Fame Canadian ice hockey defenseman best known for his long, successful career with the Montreal Canadiens and multiple Stanley Cup championships.
-
D.
John J. Haden
John J. Haden was an early 20th-century Florida horticulturist best known for developing the influential Haden mango cultivar that helped launch Florida’s commercial mango industry.
-
E.
Stuart Heisler
Stuart Heisler was an American film and television director known for his work in Hollywood from the 1930s through the 1960s, including dramas, thrillers, and war films.
- 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: Joe Freeman Triple: [Martin Freeman, hasChild, Joe Freeman]
Generated description
Joe Freeman is the son of English actor Martin Freeman.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joe Freeman Target entity description: Joe Freeman is the son of English actor Martin Freeman.
-
A.
Max Mullen
Max Mullen is an American entrepreneur best known as a co-founder of the grocery delivery company Instacart.
-
B.
Larry Robinson
Larry Robinson is an American academic and administrator best known for serving as president of Florida A&M University.
-
C.
Larry Robinson
Larry Robinson is a Hall of Fame Canadian ice hockey defenseman best known for his long, successful career with the Montreal Canadiens and multiple Stanley Cup championships.
-
D.
John J. Haden
John J. Haden was an early 20th-century Florida horticulturist best known for developing the influential Haden mango cultivar that helped launch Florida’s commercial mango industry.
-
E.
Stuart Heisler
Stuart Heisler was an American film and television director known for his work in Hollywood from the 1930s through the 1960s, including dramas, thrillers, and war films.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd97040e48190b0a87489f108810e |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb6775b008190a59e480516c3ef41 |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb75ea498819089c79e63052e9696 |
completed | March 10, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb83ba6dc8190931d691d3e354bd7 |
completed | March 10, 2026, 6:20 a.m. |
Created at: March 6, 2026, 9:54 p.m.