Triple
T16119097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Gascoyne |
E391085
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mike
Mike Gascoyne is a British motorsport engineer best known for his senior technical and design roles with several Formula One teams.
|
E1196564
|
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 | Statement: [Mike Gascoyne, givenName, Mike]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Context triple: [Mike Gascoyne, givenName, Mike]
-
A.
Mike
Mike is a character in Terrence McNally’s play "The Lisbon Traviata," which explores themes of friendship, obsession, and gay relationships.
-
B.
Mike
Mike is the young boy protagonist of the 1992 family adventure film "Radio Flyer," which centers on his imaginative efforts to escape a troubled home life with his brother.
-
C.
Mike
Mike is the nickname of the fictional character Macaulay "Mike" Connor.
-
D.
Mike
Mike is the commonly used nickname for Robert Michael Bellotti.
-
E.
Mike
Mike is the given name of Lt. Mike Stone, a fictional San Francisco homicide detective from the television series "The Streets of San Francisco."
- 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 Triple: [Mike Gascoyne, givenName, Mike]
Generated description
Mike Gascoyne is a British motorsport engineer best known for his senior technical and design roles with several Formula One teams.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mike Target entity description: Mike Gascoyne is a British motorsport engineer best known for his senior technical and design roles with several Formula One teams.
-
A.
Mike
Mike is the commonly used nickname for Robert Michael Bellotti.
-
B.
Mike
Mike is the code name for Ivy Mike, the first full-scale test of a thermonuclear (hydrogen) bomb conducted by the United States in 1952.
-
C.
Mike
Mike is the given name of Lt. Mike Stone, a fictional San Francisco homicide detective from the television series "The Streets of San Francisco."
-
D.
Mike
Mike is the central con artist protagonist in David Mamet’s 1987 psychological thriller film "House of Games."
-
E.
Mike
Mike is a common masculine given name, often used as a short form of Michael.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016d527c8190928e73661b18a914 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a61e448190be1f8c79cae6c7ee |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff3b25ba081909c396431ace865ac |
completed | May 10, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff4a2964c8190bfa8c2fa0f934abe |
completed | May 10, 2026, 2:59 a.m. |
Created at: April 10, 2026, 5 a.m.