Triple
T5317714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom |
E121591
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Peter Kingdom
Peter Kingdom is the mild-mannered, compassionate solicitor protagonist of the British television drama series "Kingdom," set in a small Norfolk town.
|
E510551
|
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: Peter Kingdom | Statement: [Kingdom, mainCharacter, Peter Kingdom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Kingdom Context triple: [Kingdom, mainCharacter, Peter Kingdom]
-
A.
Jacob King
Jacob King is the determined and enigmatic South African protagonist of the action-thriller film "Message from the King," who travels to Los Angeles to uncover the truth behind his sister’s disappearance and seek revenge.
-
B.
Jack Knight
Jack Knight is a music artist known for his guest vocal contributions and collaborations in contemporary recordings.
-
C.
Roland Caulder
Roland Caulder is an actor known for his role in the film "The Iron Mask."
-
D.
Rowland
Rowland is the given name of R. H. Macy, the 19th-century American businessman who founded the Macy's department store chain.
-
E.
Rowland
Rowland is the namesake of the Jonsson-Rowland Science Center, likely a notable figure in science or education commemorated by the institution.
- 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: Peter Kingdom Triple: [Kingdom, mainCharacter, Peter Kingdom]
Generated description
Peter Kingdom is the mild-mannered, compassionate solicitor protagonist of the British television drama series "Kingdom," set in a small Norfolk town.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peter Kingdom Target entity description: Peter Kingdom is the mild-mannered, compassionate solicitor protagonist of the British television drama series "Kingdom," set in a small Norfolk town.
-
A.
Jacob King
Jacob King is the determined and enigmatic South African protagonist of the action-thriller film "Message from the King," who travels to Los Angeles to uncover the truth behind his sister’s disappearance and seek revenge.
-
B.
Jack Knight
Jack Knight is a music artist known for his guest vocal contributions and collaborations in contemporary recordings.
-
C.
Roland Caulder
Roland Caulder is an actor known for his role in the film "The Iron Mask."
-
D.
Rowland
Rowland is the given name of R. H. Macy, the 19th-century American businessman who founded the Macy's department store chain.
-
E.
Rowland
Rowland is the namesake of the Jonsson-Rowland Science Center, likely a notable figure in science or education commemorated by the institution.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd855269ac8190bb7a9248d04f1823 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf1111f104819094d7646dec32fad2 |
completed | March 21, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_69bf11a601c481908a8cb6ea2c04d6df |
completed | March 21, 2026, 9:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf127799208190a47580ed7b9ad550 |
completed | March 21, 2026, 9:49 p.m. |
Created at: March 20, 2026, 1:59 p.m.