Triple
T20960546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Lendl |
E516229
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Samantha Frankel
Samantha Frankel is known as the wife of former world No. 1 tennis player Ivan Lendl.
|
E1459256
|
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 Frankel | Statement: [Ivan Lendl, spouse, Samantha Frankel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samantha Frankel Context triple: [Ivan Lendl, spouse, Samantha Frankel]
-
A.
Samantha Cohen
Samantha Cohen is known as the daughter of Michael Cohen, the former personal attorney to Donald Trump who became a prominent figure in investigations related to the Trump presidency.
-
B.
Samantha Finch
Samantha Finch is the daughter of acclaimed English actor Peter Finch.
-
C.
Samantha Nisenboim
Samantha Nisenboim is a film producer known for her work on the 2023 horror-comedy movie "Renfield."
-
D.
Marlena Rosenbluth
Marlena Rosenbluth is a glamorous circus performer and animal trainer who becomes the central love interest and emotional core of Sara Gruen’s novel "Water for Elephants."
-
E.
Samantha Lorraine
Samantha Lorraine is an American actress best known for her role in the Netflix coming-of-age comedy film "You Are So Not Invited to My Bat Mitzvah."
- 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 Frankel Triple: [Ivan Lendl, spouse, Samantha Frankel]
Generated description
Samantha Frankel is known as the wife of former world No. 1 tennis player Ivan Lendl.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samantha Frankel Target entity description: Samantha Frankel is known as the wife of former world No. 1 tennis player Ivan Lendl.
-
A.
Samantha Cohen
Samantha Cohen is known as the daughter of Michael Cohen, the former personal attorney to Donald Trump who became a prominent figure in investigations related to the Trump presidency.
-
B.
Samantha Finch
Samantha Finch is the daughter of acclaimed English actor Peter Finch.
-
C.
Samantha Nisenboim
Samantha Nisenboim is a film producer known for her work on the 2023 horror-comedy movie "Renfield."
-
D.
Marlena Rosenbluth
Marlena Rosenbluth is a glamorous circus performer and animal trainer who becomes the central love interest and emotional core of Sara Gruen’s novel "Water for Elephants."
-
E.
Samantha Lorraine
Samantha Lorraine is an American actress best known for her role in the Netflix coming-of-age comedy film "You Are So Not Invited to My Bat Mitzvah."
- 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_69e0b4fde6c48190af1398e7e734629e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb6f134081908b1ed48ce708f3d5 |
completed | April 21, 2026, 4:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0927969140819089027995f14d86ee |
completed | May 17, 2026, 2:27 a.m. |
| NEDg | Description generation | batch_6a0928e11bc481909b4350770db28671 |
completed | May 17, 2026, 2:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0929e0fb308190a224fe9dceb74a1c |
completed | May 17, 2026, 2:37 a.m. |
Created at: April 16, 2026, 1:31 p.m.