Triple
T12869559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maps to the Stars |
E307810
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Agatha Weiss
Agatha Weiss is a troubled, scarred young woman in the film "Maps to the Stars," whose return to Hollywood exposes dark family secrets and the toxic underbelly of celebrity culture.
|
E1007758
|
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: Agatha Weiss | Statement: [Maps to the Stars, character, Agatha Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agatha Weiss Context triple: [Maps to the Stars, character, Agatha Weiss]
-
A.
Rachel Ann Weiss
Rachel Ann Weiss is the daughter of acclaimed American actress Kathleen Turner and is known for her work as a singer-songwriter.
-
B.
Agathe Natanson
Agathe Natanson is a French actress known for her work in film, television, and theater.
-
C.
Lizzie Gottlieb
Lizzie Gottlieb is an American documentary filmmaker best known for her intimate, character-driven films exploring artists, writers, and the creative process.
-
D.
Jennifer Weiss
Jennifer Weiss is a film producer known for her work on independent movies, including the Canadian drama "Take This Waltz."
-
E.
Isabel Hatkoff
Isabel Hatkoff is the daughter of American film producer and Tribeca Film Festival co-founder Jane Rosenthal.
- 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: Agatha Weiss Triple: [Maps to the Stars, character, Agatha Weiss]
Generated description
Agatha Weiss is a troubled, scarred young woman in the film "Maps to the Stars," whose return to Hollywood exposes dark family secrets and the toxic underbelly of celebrity culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Agatha Weiss Target entity description: Agatha Weiss is a troubled, scarred young woman in the film "Maps to the Stars," whose return to Hollywood exposes dark family secrets and the toxic underbelly of celebrity culture.
-
A.
Rachel Ann Weiss
Rachel Ann Weiss is the daughter of acclaimed American actress Kathleen Turner and is known for her work as a singer-songwriter.
-
B.
Agathe Natanson
Agathe Natanson is a French actress known for her work in film, television, and theater.
-
C.
Lizzie Gottlieb
Lizzie Gottlieb is an American documentary filmmaker best known for her intimate, character-driven films exploring artists, writers, and the creative process.
-
D.
Jennifer Weiss
Jennifer Weiss is a film producer known for her work on independent movies, including the Canadian drama "Take This Waltz."
-
E.
Isabel Hatkoff
Isabel Hatkoff is the daughter of American film producer and Tribeca Film Festival co-founder Jane Rosenthal.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708f510c8190b4c64dc340420e85 |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb26eb08190912d0b44c345bf41 |
completed | May 3, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69f69df1032881909255e506ddfd9c9f |
completed | May 3, 2026, 12:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69ea645a0819095edc112b9ed9bff |
completed | May 3, 2026, 1:02 a.m. |
Created at: April 9, 2026, 5:38 p.m.