Triple
T13814906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heartland |
E331987
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Tom Cox
Tom Cox is a television producer best known for his executive production work on the Canadian family drama series "Heartland."
|
E1068811
|
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 Cox | Statement: [Heartland, executiveProducer, Tom Cox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Cox Context triple: [Heartland, executiveProducer, Tom Cox]
-
A.
Perry Cox
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
-
B.
Will Healey
Will Healey is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Healey.
-
C.
Al Clark
Al Clark was an American film editor best known for his work on classic Hollywood films, including the 1939 political drama "Mr. Smith Goes to Washington."
-
D.
Al Clark
Al Clark is a film producer best known for his work on the acclaimed Australian comedy-drama "The Adventures of Priscilla, Queen of the Desert."
-
E.
Hartland Snyder
Hartland Snyder was an American theoretical physicist known for his early work on black hole physics and for being one of J. Robert Oppenheimer’s notable doctoral students.
- 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 Cox Triple: [Heartland, executiveProducer, Tom Cox]
Generated description
Tom Cox is a television producer best known for his executive production work on the Canadian family drama series "Heartland."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Cox Target entity description: Tom Cox is a television producer best known for his executive production work on the Canadian family drama series "Heartland."
-
A.
Perry Cox
Perry Cox is a sarcastic, tough-love attending physician and mentor on the medical comedy-drama series "Scrubs."
-
B.
Will Healey
Will Healey is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Healey.
-
C.
Al Clark
Al Clark was an American film editor best known for his work on classic Hollywood films, including the 1939 political drama "Mr. Smith Goes to Washington."
-
D.
Al Clark
Al Clark is a film producer best known for his work on the acclaimed Australian comedy-drama "The Adventures of Priscilla, Queen of the Desert."
-
E.
Hartland Snyder
Hartland Snyder was an American theoretical physicist known for his early work on black hole physics and for being one of J. Robert Oppenheimer’s notable doctoral students.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c70454a8819097b5e5091f84be33 |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c8d477f881908f8cfd2783e7f10f |
completed | May 3, 2026, 10:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7ca27ffd4819080bccd6bfd88ddb3 |
completed | May 3, 2026, 10:20 p.m. |
Created at: April 9, 2026, 10:12 p.m.