Triple
T2882042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gina Gershon |
E59417
|
entity |
| Predicate | hasSibling |
P363
|
FINISHED |
| Object |
Tracy Gershon
Tracy Gershon is an American music industry executive and talent scout known for her work in country music and artist development.
|
E411029
|
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: Tracy Gershon | Statement: [Gina Gershon, hasSibling, Tracy Gershon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tracy Gershon Context triple: [Gina Gershon, hasSibling, Tracy Gershon]
-
A.
Tracy Reiner
Tracy Reiner is an American actress known for her roles in films such as "A League of Their Own" and "When Harry Met Sally...."
-
B.
Stacey Mindich
Stacey Mindich is a Tony Award–winning American theater producer best known for shepherding the hit Broadway musical "Dear Evan Hansen."
-
C.
Tracy Benchley
Tracy Benchley is a child of American author and screenwriter Peter Benchley, best known for writing the novel "Jaws."
-
D.
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.
-
E.
Liz Gorinsky
Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
- 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: Tracy Gershon Triple: [Gina Gershon, hasSibling, Tracy Gershon]
Generated description
Tracy Gershon is an American music industry executive and talent scout known for her work in country music and artist development.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tracy Gershon Target entity description: Tracy Gershon is an American music industry executive and talent scout known for her work in country music and artist development.
-
A.
Tracy Reiner
Tracy Reiner is an American actress known for her roles in films such as "A League of Their Own" and "When Harry Met Sally...."
-
B.
Stacey Mindich
Stacey Mindich is a Tony Award–winning American theater producer best known for shepherding the hit Broadway musical "Dear Evan Hansen."
-
C.
Tracy Benchley
Tracy Benchley is a child of American author and screenwriter Peter Benchley, best known for writing the novel "Jaws."
-
D.
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.
-
E.
Liz Gorinsky
Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe02aa5948190a2e0bd9168232bd5 |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5627344648190b2794d4e71524bf4 |
completed | March 14, 2026, 1:28 p.m. |
| NEDg | Description generation | batch_69b5665f491c8190ad6c593d34b54dca |
completed | March 14, 2026, 1:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b566b5178c8190b0271114805f1ec0 |
completed | March 14, 2026, 1:46 p.m. |
Created at: March 6, 2026, 10:03 p.m.