Triple
T10464977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stardust (1974 film) |
E246768
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Mike Menary
Mike Menary is a fictional character appearing in the 1974 British musical drama film "Stardust."
|
E866248
|
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 Menary | Statement: [Stardust (1974 film), character, Mike Menary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Menary Context triple: [Stardust (1974 film), character, Mike Menary]
-
A.
Bill Manning
Bill Manning is an American sports executive best known for serving as president of Major League Soccer clubs, including Toronto FC and previously Real Salt Lake.
-
B.
Mike Malloy
Mike Malloy is a progressive American radio talk show host known for his outspoken, left-leaning political commentary and work on various liberal talk radio networks.
-
C.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
D.
Anthony McHenry
Anthony McHenry is an American professional basketball player best known for his long, successful career in Japan’s B.League, particularly as a key contributor to the Ryukyu Golden Kings.
-
E.
Doug Bowne
Doug Bowne is a musician best known for his work with the new wave band Tom Tom Club.
- 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 Menary Triple: [Stardust (1974 film), character, Mike Menary]
Generated description
Mike Menary is a fictional character appearing in the 1974 British musical drama film "Stardust."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Menary Target entity description: Mike Menary is a fictional character appearing in the 1974 British musical drama film "Stardust."
-
A.
Bill Manning
Bill Manning is an American sports executive best known for serving as president of Major League Soccer clubs, including Toronto FC and previously Real Salt Lake.
-
B.
Mike Malloy
Mike Malloy is a progressive American radio talk show host known for his outspoken, left-leaning political commentary and work on various liberal talk radio networks.
-
C.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
D.
Anthony McHenry
Anthony McHenry is an American professional basketball player best known for his long, successful career in Japan’s B.League, particularly as a key contributor to the Ryukyu Golden Kings.
-
E.
Doug Bowne
Doug Bowne is a musician best known for his work with the new wave band Tom Tom Club.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50886c2a8819086da6c08356ec6bf |
completed | April 7, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89fe6129881908c658ff977e68135 |
completed | April 10, 2026, 6:59 a.m. |
| NEDg | Description generation | batch_69d8a43ae8a48190b1c05b6a91dfed9a |
completed | April 10, 2026, 7:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d8b8fe1b9c8190b5a4787797ad7120 |
completed | April 10, 2026, 8:46 a.m. |
Created at: April 6, 2026, 12:19 p.m.