Triple
T15646992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Keller |
E376204
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Samantha
Samantha is a character portrayed by American actress Rachel Keller, known for her roles in television series such as "Legion" and "Fargo."
|
E1170909
|
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: Samantha | Statement: [Rachel Keller, playedCharacter, Samantha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samantha Context triple: [Rachel Keller, playedCharacter, Samantha]
-
A.
Samantha
Samantha is a central character in the psychological thriller film "Enter Nowhere," where she becomes trapped in a mysterious cabin in the woods alongside two strangers as they unravel a time-bending mystery.
-
B.
Samantha
Samantha is the middle name of the fictional socialite Tracy Samantha Lord from the classic film and play "The Philadelphia Story."
-
C.
Samantha
Samantha is an AI character, likely designed as a virtual persona with human-like conversational abilities and personality traits.
-
D.
Samantha
Samantha is a feminine given name of Aramaic origin meaning "listener" or "heard by God," widely used in English-speaking countries.
-
E.
Samantha
"Samantha" is a jazz composition famously performed by British trumpeter and bandleader Kenny Ball.
- 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: Samantha Triple: [Rachel Keller, playedCharacter, Samantha]
Generated description
Samantha is a character portrayed by American actress Rachel Keller, known for her roles in television series such as "Legion" and "Fargo."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samantha Target entity description: Samantha is a character portrayed by American actress Rachel Keller, known for her roles in television series such as "Legion" and "Fargo."
-
A.
Samantha
Samantha is the middle name of the fictional socialite Tracy Samantha Lord from the classic film and play "The Philadelphia Story."
-
B.
Samantha
Samantha is an AI character, likely designed as a virtual persona with human-like conversational abilities and personality traits.
-
C.
Samantha
Samantha is a central character in the psychological thriller film "Enter Nowhere," where she becomes trapped in a mysterious cabin in the woods alongside two strangers as they unravel a time-bending mystery.
-
D.
Samantha
Samantha is a feminine given name of Aramaic origin meaning "listener" or "heard by God," widely used in English-speaking countries.
-
E.
Samantha
"Samantha" is a jazz composition famously performed by British trumpeter and bandleader Kenny Ball.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ed079e48190b86ad7b66755fc1c |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6fa2b0b881908fa7af973ee0bb6f |
completed | May 9, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff707d1db4819097aa9402ce0abb97 |
completed | May 9, 2026, 5:35 p.m. |
Created at: April 10, 2026, 4:15 a.m.