Triple
T5590765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halloweentown |
E146870
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Jon Cooksey
Jon Cooksey is a television and film writer best known for co-writing the popular Disney Channel movie "Halloweentown."
|
E607845
|
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: Jon Cooksey | Statement: [Halloweentown, screenwriter, Jon Cooksey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jon Cooksey Context triple: [Halloweentown, screenwriter, Jon Cooksey]
-
A.
Donald Cooksey
Donald Cooksey was an American physicist known for his work in nuclear physics and his leadership role at the MIT Radiation Laboratory during World War II.
-
B.
Douglas Cook
Douglas Cook was an American screenwriter best known for co-writing action and thriller films such as "The Rock" and "Double Jeopardy."
-
C.
Rob Cook
Rob Cook is a renowned computer graphics researcher and Pixar executive known for his pioneering work in rendering and visual effects.
-
D.
Ray Cusick
Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
-
E.
Karl Cook
Karl Cook is an American equestrian and businessman known for his competitive show jumping career and his former marriage to actress Kaley Cuoco.
- 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: Jon Cooksey Triple: [Halloweentown, screenwriter, Jon Cooksey]
Generated description
Jon Cooksey is a television and film writer best known for co-writing the popular Disney Channel movie "Halloweentown."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jon Cooksey Target entity description: Jon Cooksey is a television and film writer best known for co-writing the popular Disney Channel movie "Halloweentown."
-
A.
Donald Cooksey
Donald Cooksey was an American physicist known for his work in nuclear physics and his leadership role at the MIT Radiation Laboratory during World War II.
-
B.
Douglas Cook
Douglas Cook was an American screenwriter best known for co-writing action and thriller films such as "The Rock" and "Double Jeopardy."
-
C.
Rob Cook
Rob Cook is a renowned computer graphics researcher and Pixar executive known for his pioneering work in rendering and visual effects.
-
D.
Ray Cusick
Ray Cusick was a British designer best known for creating the iconic look of the Daleks in the long-running science fiction television series Doctor Who.
-
E.
Karl Cook
Karl Cook is an American equestrian and businessman known for his competitive show jumping career and his former marriage to actress Kaley Cuoco.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020a1d4cc8190a52264dfba6aa011 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e3ff314c8190b66f8b0a7ae3c039 |
completed | March 27, 2026, 8:09 p.m. |
| NEDg | Description generation | batch_69c6e7c75140819082a32e4662e0b07c |
completed | March 27, 2026, 8:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6e8881b848190bd6184aeaf311d24 |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 22, 2026, 3:38 p.m.