Triple
T11947463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirens |
E284337
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Brian Fillis
Brian Fillis is a British television writer and dramatist known for creating the crime drama series "Sirens" and other character-driven TV works.
|
E955916
|
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: Brian Fillis | Statement: [Sirens, creator, Brian Fillis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Fillis Context triple: [Sirens, creator, Brian Fillis]
-
A.
Hilary Minc
Hilary Minc was a prominent Polish communist politician and economist who played a leading role in shaping Poland’s post-World War II socialist economy.
-
B.
Karen Filippelli
Karen Filippelli is a character from the U.S. version of "The Office," known as a saleswoman at Dunder Mifflin and a former love interest of Jim Halpert.
-
C.
Hilary Shor
Hilary Shor is a film producer best known for her work on acclaimed features such as the dystopian drama "Children of Men."
-
D.
Tully Friedman
Tully Friedman is an American financier and private equity investor best known as the co-founder of the investment firm Hellman & Friedman.
-
E.
Kim Kelly
Kim Kelly is a tough, rebellious high school student and member of the "freaks" clique in the cult TV series *Freaks and Geeks*.
- 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: Brian Fillis Triple: [Sirens, creator, Brian Fillis]
Generated description
Brian Fillis is a British television writer and dramatist known for creating the crime drama series "Sirens" and other character-driven TV works.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brian Fillis Target entity description: Brian Fillis is a British television writer and dramatist known for creating the crime drama series "Sirens" and other character-driven TV works.
-
A.
Hilary Minc
Hilary Minc was a prominent Polish communist politician and economist who played a leading role in shaping Poland’s post-World War II socialist economy.
-
B.
Karen Filippelli
Karen Filippelli is a character from the U.S. version of "The Office," known as a saleswoman at Dunder Mifflin and a former love interest of Jim Halpert.
-
C.
Hilary Shor
Hilary Shor is a film producer best known for her work on acclaimed features such as the dystopian drama "Children of Men."
-
D.
Tully Friedman
Tully Friedman is an American financier and private equity investor best known as the co-founder of the investment firm Hellman & Friedman.
-
E.
Kim Kelly
Kim Kelly is a tough, rebellious high school student and member of the "freaks" clique in the cult TV series *Freaks and Geeks*.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903456ec0819082b8b10755a6b732 |
completed | April 10, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f458e003a0819082d052fd0bb88d8b |
completed | May 1, 2026, 7:40 a.m. |
| NEDg | Description generation | batch_69f4645a7038819089d7533715f8a430 |
completed | May 1, 2026, 8:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f4664ff9608190b23e29b3e5c1c326 |
completed | May 1, 2026, 8:37 a.m. |
Created at: April 8, 2026, 9:45 p.m.