Triple
T8251171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resnick |
E192958
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sarah Resnick
Sarah Resnick is a notable individual recognized as a prominent bearer of the surname Resnick.
|
E734089
|
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: Sarah Resnick | Statement: [Resnick, hasNotableBearer, Sarah Resnick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Resnick Context triple: [Resnick, hasNotableBearer, Sarah Resnick]
-
A.
Rachel Resnick
Rachel Resnick is an American author and memoirist known for her candid, often humorous explorations of personal relationships and emotional vulnerability.
-
B.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
-
C.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
-
D.
Lauren Resnick
Lauren Resnick is an American educational psychologist known for her influential research on learning, cognition, and the design of effective educational practices.
-
E.
Amy Stechler
Amy Stechler is an American documentary filmmaker and editor known for her early collaborations with Ken Burns on historical films.
- 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: Sarah Resnick Triple: [Resnick, hasNotableBearer, Sarah Resnick]
Generated description
Sarah Resnick is a notable individual recognized as a prominent bearer of the surname Resnick.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Resnick Target entity description: Sarah Resnick is a notable individual recognized as a prominent bearer of the surname Resnick.
-
A.
Rachel Resnick
Rachel Resnick is an American author and memoirist known for her candid, often humorous explorations of personal relationships and emotional vulnerability.
-
B.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
-
C.
Ann Rosener
Ann Rosener was an American photographer best known for her documentary images of home-front life and industry during World War II, particularly through her work for U.S. government agencies.
-
D.
Lauren Resnick
Lauren Resnick is an American educational psychologist known for her influential research on learning, cognition, and the design of effective educational practices.
-
E.
Amy Stechler
Amy Stechler is an American documentary filmmaker and editor known for her early collaborations with Ken Burns on historical films.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78c935408190b9196a849a8d3a3e |
completed | March 31, 2026, 7:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1cc9be088190b2b51281bc2f71bf |
completed | April 2, 2026, 7:37 a.m. |
| NEDg | Description generation | batch_69ce1e3a269481908ea191ff28ea1313 |
completed | April 2, 2026, 7:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1ef9fb208190a50b4d8a595f5fdb |
completed | April 2, 2026, 7:47 a.m. |
Created at: March 30, 2026, 5:48 p.m.