Triple
T12613413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big House |
E301184
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Tom Kennedy
Tom Kennedy is an actor known for his role in the film "The Big House."
|
E993158
|
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: Tom Kennedy | Statement: [The Big House, castMember, Tom Kennedy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Kennedy Context triple: [The Big House, castMember, Tom Kennedy]
-
A.
Kevin Kennedy
Kevin Kennedy is a screenwriter known for co-writing the 2004 drama film "The Assassination of Richard Nixon."
-
B.
Steve Kennedy
Steve Kennedy is a theatrical sound designer known for his work on major stage productions, including the Broadway musical "On Your Feet!".
-
C.
Sam Kennedy
Sam Kennedy is a Major League Baseball executive best known for serving as the president and CEO of the Boston Red Sox.
-
D.
Christopher G. Kennedy
Christopher G. Kennedy is an American businessman and member of the Kennedy political family, known for his work in real estate and public service in Illinois.
-
E.
David Kennedy
David Kennedy is a prominent cybersecurity expert and penetration tester best known as the creator of the Social-Engineer Toolkit and founder of the security firm TrustedSec.
- 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: Tom Kennedy Triple: [The Big House, castMember, Tom Kennedy]
Generated description
Tom Kennedy is an actor known for his role in the film "The Big House."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Kennedy Target entity description: Tom Kennedy is an actor known for his role in the film "The Big House."
-
A.
Kevin Kennedy
Kevin Kennedy is a screenwriter known for co-writing the 2004 drama film "The Assassination of Richard Nixon."
-
B.
Steve Kennedy
Steve Kennedy is a theatrical sound designer known for his work on major stage productions, including the Broadway musical "On Your Feet!".
-
C.
Sam Kennedy
Sam Kennedy is a Major League Baseball executive best known for serving as the president and CEO of the Boston Red Sox.
-
D.
Christopher G. Kennedy
Christopher G. Kennedy is an American businessman and member of the Kennedy political family, known for his work in real estate and public service in Illinois.
-
E.
David Kennedy
David Kennedy is a prominent cybersecurity expert and penetration tester best known as the creator of the Social-Engineer Toolkit and founder of the security firm TrustedSec.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c2e5b88190a7cc16002b218d8a |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ed1044c8190bbe881d32a4bf29e |
completed | May 2, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f6617479ec819080eac67abc9bc435 |
completed | May 2, 2026, 8:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f662695a348190b9911a19dfc9e779 |
completed | May 2, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:12 p.m.