Triple
T13481321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Someone to Watch Over Me |
E318378
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Mike Keegan
Mike Keegan is the New York City police detective protagonist of the 1987 neo-noir thriller film "Someone to Watch Over Me."
|
E1119391
|
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: Mike Keegan | Statement: [Someone to Watch Over Me, mainCharacter, Mike Keegan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Keegan Context triple: [Someone to Watch Over Me, mainCharacter, Mike Keegan]
-
A.
Joe Kerrigan
Joe Kerrigan is a former Major League Baseball pitching coach and brief Boston Red Sox manager best known for his long coaching career with several MLB teams.
-
B.
Tom Keogh
Tom Keogh was a noted costume designer best known for his work in mid-20th-century theatre and film productions.
-
C.
Mick Burke
Mick Burke was a renowned British mountaineer best known for his high-altitude climbs in the Himalayas and his work as a climbing cameraman on major expeditions.
-
D.
Joe Keenan
Joe Keenan is an American television writer, producer, and novelist best known for his work on the sitcom "Frasier" and other acclaimed comedy projects.
-
E.
Kevin Duggan
Kevin Duggan is a relatively obscure individual whose name is shared with multiple people across different professions, such as sports and public service.
- 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: Mike Keegan Triple: [Someone to Watch Over Me, mainCharacter, Mike Keegan]
Generated description
Mike Keegan is the New York City police detective protagonist of the 1987 neo-noir thriller film "Someone to Watch Over Me."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Keegan Target entity description: Mike Keegan is the New York City police detective protagonist of the 1987 neo-noir thriller film "Someone to Watch Over Me."
-
A.
Joe Kerrigan
Joe Kerrigan is a former Major League Baseball pitching coach and brief Boston Red Sox manager best known for his long coaching career with several MLB teams.
-
B.
Tom Keogh
Tom Keogh was a noted costume designer best known for his work in mid-20th-century theatre and film productions.
-
C.
Mick Burke
Mick Burke was a renowned British mountaineer best known for his high-altitude climbs in the Himalayas and his work as a climbing cameraman on major expeditions.
-
D.
Joe Keenan
Joe Keenan is an American television writer, producer, and novelist best known for his work on the sitcom "Frasier" and other acclaimed comedy projects.
-
E.
Kevin Duggan
Kevin Duggan is a relatively obscure individual whose name is shared with multiple people across different professions, such as sports and public service.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf36c6b08190ba99400600e0b662 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cce10c88190bf25404fc4c75bbf |
completed | May 8, 2026, 4:18 p.m. |
| NEDg | Description generation | batch_69fe1903c0f88190b6f1a081047506d5 |
completed | May 8, 2026, 5:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe1980179481908b9f97e2f474e00d |
completed | May 8, 2026, 5:12 p.m. |
Created at: April 9, 2026, 9:42 p.m.