Triple
T16315796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTU |
E396169
|
entity |
| Predicate | employerOfFictionalCharacter |
P76778
|
FINISHED |
| Object |
Karen Hayes
Karen Hayes is a fictional intelligence analyst and later director at the Counter Terrorist Unit (CTU) in the television series "24."
|
E1275913
|
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: Karen Hayes | Statement: [CTU, employerOfFictionalCharacter, Karen Hayes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Hayes Context triple: [CTU, employerOfFictionalCharacter, Karen Hayes]
-
A.
Laura Hayes
Laura Hayes is an American actress and comedian best known for her role in the ensemble cast of the film "Beauty Shop."
-
B.
Kate Fahy
Kate Fahy is a British actress and theatre director known for her extensive stage work and long-term partnership with actor Jonathan Pryce.
-
C.
Bridget Hayward
Bridget Hayward is the daughter of acclaimed American actress Margaret Sullavan and producer Leland Hayward.
-
D.
Kate Hennessy
Kate Hennessy is an American writer and the granddaughter of Catholic social activist Dorothy Day, known for her memoirs and work chronicling her family’s legacy.
-
E.
Mary Heneghan
Mary Heneghan is best known as the wife of renowned British broadcaster and talk show host Michael Parkinson.
- 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: Karen Hayes Triple: [CTU, employerOfFictionalCharacter, Karen Hayes]
Generated description
Karen Hayes is a fictional intelligence analyst and later director at the Counter Terrorist Unit (CTU) in the television series "24."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karen Hayes Target entity description: Karen Hayes is a fictional intelligence analyst and later director at the Counter Terrorist Unit (CTU) in the television series "24."
-
A.
Laura Hayes
Laura Hayes is an American actress and comedian best known for her role in the ensemble cast of the film "Beauty Shop."
-
B.
Kate Fahy
Kate Fahy is a British actress and theatre director known for her extensive stage work and long-term partnership with actor Jonathan Pryce.
-
C.
Bridget Hayward
Bridget Hayward is the daughter of acclaimed American actress Margaret Sullavan and producer Leland Hayward.
-
D.
Kate Hennessy
Kate Hennessy is an American writer and the granddaughter of Catholic social activist Dorothy Day, known for her memoirs and work chronicling her family’s legacy.
-
E.
Mary Heneghan
Mary Heneghan is best known as the wife of renowned British broadcaster and talk show host Michael Parkinson.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b1e9988190a1dce9f1ed7031df |
completed | April 17, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01d273f37c8190bbad1ee6a0dc215f |
completed | May 11, 2026, 12:58 p.m. |
| NEDg | Description generation | batch_6a01d89932cc8190b3fd0ee72567cf46 |
completed | May 11, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01d9741c348190ab926699e1b6a48f |
completed | May 11, 2026, 1:28 p.m. |
Created at: April 10, 2026, 5:06 a.m.