Triple
T13557645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krysten Ritter |
E323816
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Krysten
Krysten is a feminine given name most notably associated with American actress and author Krysten Ritter.
|
E1047005
|
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: Krysten | Statement: [Krysten Ritter, givenName, Krysten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krysten Context triple: [Krysten Ritter, givenName, Krysten]
-
A.
Kristen
Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
-
B.
Kristen
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
C.
Kristen
Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
-
D.
Kristen
Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
-
E.
Kirsten
Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
- 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: Krysten Triple: [Krysten Ritter, givenName, Krysten]
Generated description
Krysten is a feminine given name most notably associated with American actress and author Krysten Ritter.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Krysten Target entity description: Krysten is a feminine given name most notably associated with American actress and author Krysten Ritter.
-
A.
Kristen
Kristen is the birth name of Kris Jenner, the American television personality and matriarch of the Kardashian–Jenner family.
-
B.
Kristen
Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
-
C.
Kristen
Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
D.
Kristen
Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
-
E.
Kirsten
Kirsten is the first name of Kirsten Gillibrand, a prominent American politician and U.S. Senator from New York.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaff4223c8190801d153ae8f94c73 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75da95b7c8190af4fae155f01d3af |
completed | May 3, 2026, 2:37 p.m. |
| NEDg | Description generation | batch_69f75ffd5a088190967dae3262a22302 |
completed | May 3, 2026, 2:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f76072de148190b8911df91caa87b5 |
completed | May 3, 2026, 2:49 p.m. |
Created at: April 9, 2026, 9:47 p.m.