Triple
T3314008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Game of Thrones season 4 |
E69636
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Bernadette Caulfield
Bernadette Caulfield is an American television producer best known for her work as a senior producer on the HBO fantasy series "Game of Thrones."
|
E347382
|
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: Bernadette Caulfield | Statement: [Game of Thrones season 4, executiveProducer, Bernadette Caulfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernadette Caulfield Context triple: [Game of Thrones season 4, executiveProducer, Bernadette Caulfield]
-
A.
Bernadette Wall
Bernadette Wall is an individual notable enough to be recognized as a prominent bearer of the surname Wall.
-
B.
Mary Durkan
Mary Durkan is an Irish politician known for her involvement in local and national public affairs.
-
C.
Elizabeth McLaughlin
Elizabeth McLaughlin is an American actress known for her roles in television series such as the psychological drama "Hand of God."
-
D.
Mary Cleary
Mary Cleary was the wife of Commodore John Barry, an early U.S. naval officer often called the "Father of the American Navy."
-
E.
Mary Mulhern
Mary Mulhern was an American actress best known for her brief Hollywood career in the silent film era and her marriage to actor Jack Pickford.
- 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: Bernadette Caulfield Triple: [Game of Thrones season 4, executiveProducer, Bernadette Caulfield]
Generated description
Bernadette Caulfield is an American television producer best known for her work as a senior producer on the HBO fantasy series "Game of Thrones."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bernadette Caulfield Target entity description: Bernadette Caulfield is an American television producer best known for her work as a senior producer on the HBO fantasy series "Game of Thrones."
-
A.
Bernadette Wall
Bernadette Wall is an individual notable enough to be recognized as a prominent bearer of the surname Wall.
-
B.
Mary Durkan
Mary Durkan is an Irish politician known for her involvement in local and national public affairs.
-
C.
Elizabeth McLaughlin
Elizabeth McLaughlin is an American actress known for her roles in television series such as the psychological drama "Hand of God."
-
D.
Mary Cleary
Mary Cleary was the wife of Commodore John Barry, an early U.S. naval officer often called the "Father of the American Navy."
-
E.
Mary Mulhern
Mary Mulhern was an American actress best known for her brief Hollywood career in the silent film era and her marriage to actor Jack Pickford.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb10f97b48190afb9c3864faf8cb2 |
completed | March 8, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3f760348190abd8854c369cb41b |
completed | March 12, 2026, 5:12 p.m. |
| NEDg | Description generation | batch_69b2fa1dafe8819094905ac930fd1761 |
completed | March 12, 2026, 5:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b312b6e224819080957998acbed524 |
completed | March 12, 2026, 7:23 p.m. |
Created at: March 8, 2026, 3:11 p.m.