Triple
T2643671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Tremaine |
E62935
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Gabrielle Anwar
Gabrielle Anwar is a British-American actress best known for roles in projects like "Scent of a Woman," "The Tudors," and "Burn Notice."
|
E285196
|
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: Gabrielle Anwar | Statement: [Lady Tremaine, portrayedBy, Gabrielle Anwar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabrielle Anwar Context triple: [Lady Tremaine, portrayedBy, Gabrielle Anwar]
-
A.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
B.
Najwa Nimri
Najwa Nimri is a Spanish actress and singer best known internationally for her roles in acclaimed series like "Money Heist" and "Vis a Vis."
-
C.
Lara Alameddine
Lara Alameddine is a film producer known for her work on the financial thriller "Money Monster."
-
D.
Rebekah Elmaloglou
Rebekah Elmaloglou is an Australian actress best known for her long-running role as Terese Willis on the soap opera "Neighbours."
-
E.
Daniela Ruah
Daniela Ruah is a Portuguese-American actress best known for playing Special Agent Kensi Blye on the television series "NCIS: Los Angeles."
- 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: Gabrielle Anwar Triple: [Lady Tremaine, portrayedBy, Gabrielle Anwar]
Generated description
Gabrielle Anwar is a British-American actress best known for roles in projects like "Scent of a Woman," "The Tudors," and "Burn Notice."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gabrielle Anwar Target entity description: Gabrielle Anwar is a British-American actress best known for roles in projects like "Scent of a Woman," "The Tudors," and "Burn Notice."
-
A.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
B.
Najwa Nimri
Najwa Nimri is a Spanish actress and singer best known internationally for her roles in acclaimed series like "Money Heist" and "Vis a Vis."
-
C.
Lara Alameddine
Lara Alameddine is a film producer known for her work on the financial thriller "Money Monster."
-
D.
Rebekah Elmaloglou
Rebekah Elmaloglou is an Australian actress best known for her long-running role as Terese Willis on the soap opera "Neighbours."
-
E.
Daniela Ruah
Daniela Ruah is a Portuguese-American actress best known for playing Special Agent Kensi Blye on the television series "NCIS: Los Angeles."
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd90046dc81908bab3440733f1e98 |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98c2bde8819085fbe1e5221be88d |
completed | March 10, 2026, 4:06 a.m. |
| NEDg | Description generation | batch_69af992fafc88190a95b09b7aebeb5a9 |
completed | March 10, 2026, 4:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af9983ff8881909273212c6fc6a218 |
completed | March 10, 2026, 4:09 a.m. |
Created at: March 6, 2026, 9:53 p.m.