Triple
T2096903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resnick Pavilion |
E37002
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Lynda Resnick
Lynda Resnick is an American billionaire businesswoman and philanthropist known for co-owning The Wonderful Company and for her extensive arts and cultural patronage.
|
E248729
|
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: Lynda Resnick | Statement: [Resnick Pavilion, namedAfter, Lynda Resnick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lynda Resnick Context triple: [Resnick Pavilion, namedAfter, Lynda Resnick]
-
A.
Lynda Dryden
Lynda Dryden is the wife of former NHL goaltender and Canadian politician Ken Dryden.
-
B.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
C.
Amy Landecker
Amy Landecker is an American actress best known for her role as Sarah Pfefferman on the television series "Transparent."
-
D.
Diandra Luker
Diandra Luker is a film producer and the former wife of American actor Michael Douglas.
-
E.
Melissa Rosenberg
Melissa Rosenberg is an American screenwriter and producer best known for adapting the Twilight Saga films and creating the Marvel television series Jessica Jones.
- 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: Lynda Resnick Triple: [Resnick Pavilion, namedAfter, Lynda Resnick]
Generated description
Lynda Resnick is an American billionaire businesswoman and philanthropist known for co-owning The Wonderful Company and for her extensive arts and cultural patronage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lynda Resnick Target entity description: Lynda Resnick is an American billionaire businesswoman and philanthropist known for co-owning The Wonderful Company and for her extensive arts and cultural patronage.
-
A.
Lynda Dryden
Lynda Dryden is the wife of former NHL goaltender and Canadian politician Ken Dryden.
-
B.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
C.
Amy Landecker
Amy Landecker is an American actress best known for her role as Sarah Pfefferman on the television series "Transparent."
-
D.
Diandra Luker
Diandra Luker is a film producer and the former wife of American actor Michael Douglas.
-
E.
Melissa Rosenberg
Melissa Rosenberg is an American screenwriter and producer best known for adapting the Twilight Saga films and creating the Marvel television series Jessica Jones.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9cb84481909fe0a66c020b8864 |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6aea7f58819081790c08791a5841 |
completed | March 9, 2026, 6:38 a.m. |
| NEDg | Description generation | batch_69ae6b9da51c819085beb79a14f5d8b5 |
completed | March 9, 2026, 6:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae6c2a465c8190a9fe2a465e9ac3f0 |
completed | March 9, 2026, 6:43 a.m. |
Created at: March 4, 2026, 7:43 p.m.