Triple
T12510407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliza Dushku |
E299060
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Dana Tasker
Dana Tasker is the teenage daughter of secret agent Harry Tasker in the action-comedy film "True Lies."
|
E986905
|
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: Dana Tasker | Statement: [Eliza Dushku, playedCharacter, Dana Tasker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dana Tasker Context triple: [Eliza Dushku, playedCharacter, Dana Tasker]
-
A.
Dana Congdon
Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
-
B.
Denise Huth
Denise Huth is a television producer best known for her long-running work as an executive producer on AMC’s The Walking Dead franchise and its related spin-offs.
-
C.
Danelle Morton
Danelle Morton is an American journalist and author known for co-writing celebrity memoirs and nonfiction books, including collaborating with Lynne Spears.
-
D.
Jennifer Cossitt
Jennifer Cossitt is a Canadian politician who has served as the elected representative for the Leeds—Grenville electoral district.
-
E.
Colleen Ahland
Colleen Ahland is a linguist known for her research on the Koman languages of Ethiopia and Sudan, focusing on their documentation, description, and classification.
- 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: Dana Tasker Triple: [Eliza Dushku, playedCharacter, Dana Tasker]
Generated description
Dana Tasker is the teenage daughter of secret agent Harry Tasker in the action-comedy film "True Lies."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dana Tasker Target entity description: Dana Tasker is the teenage daughter of secret agent Harry Tasker in the action-comedy film "True Lies."
-
A.
Dana Congdon
Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
-
B.
Denise Huth
Denise Huth is a television producer best known for her long-running work as an executive producer on AMC’s The Walking Dead franchise and its related spin-offs.
-
C.
Danelle Morton
Danelle Morton is an American journalist and author known for co-writing celebrity memoirs and nonfiction books, including collaborating with Lynne Spears.
-
D.
Jennifer Cossitt
Jennifer Cossitt is a Canadian politician who has served as the elected representative for the Leeds—Grenville electoral district.
-
E.
Colleen Ahland
Colleen Ahland is a linguist known for her research on the Koman languages of Ethiopia and Sudan, focusing on their documentation, description, and classification.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541d6e508190a4992f328e077467 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb94d608190aae4c8ec39556362 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce1b0ec8190bcbd245255e548b5 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64da735f48190b051ce173c13e5b2 |
completed | May 2, 2026, 7:16 p.m. |
Created at: April 8, 2026, 9:57 p.m.