Triple
T11947483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirens |
E284337
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Maxine Fox
Maxine Fox is a fictional character from the British police drama series "Sirens."
|
E1034092
|
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: Maxine Fox | Statement: [Sirens, character, Maxine Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maxine Fox Context triple: [Sirens, character, Maxine Fox]
-
A.
Maxine Albro
Maxine Albro was an American muralist and painter associated with the New Deal era, best known for her vibrant frescoes and contributions to public art in San Francisco.
-
B.
Louise Glaum
Louise Glaum was a prominent American silent film actress of the 1910s and early 1920s, best known for her sophisticated "vamp" roles in melodramas.
-
C.
Maud Ellen Dixon
Maud Ellen Dixon was the wife of New Zealand physicist and science administrator Ernest Marsden.
-
D.
Babette Dell
Babette Dell is a quirky, fast-talking resident of Stars Hollow on the television series "Gilmore Girls," known for being Lorelai Gilmore’s close friend and neighbor.
-
E.
Myrna Fahey
Myrna Fahey was an American actress known for her film and television roles in the 1950s and 1960s, often appearing in comedies and dramas.
- 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: Maxine Fox Triple: [Sirens, character, Maxine Fox]
Generated description
Maxine Fox is a fictional character from the British police drama series "Sirens."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maxine Fox Target entity description: Maxine Fox is a fictional character from the British police drama series "Sirens."
-
A.
Maxine Albro
Maxine Albro was an American muralist and painter associated with the New Deal era, best known for her vibrant frescoes and contributions to public art in San Francisco.
-
B.
Louise Glaum
Louise Glaum was a prominent American silent film actress of the 1910s and early 1920s, best known for her sophisticated "vamp" roles in melodramas.
-
C.
Maud Ellen Dixon
Maud Ellen Dixon was the wife of New Zealand physicist and science administrator Ernest Marsden.
-
D.
Babette Dell
Babette Dell is a quirky, fast-talking resident of Stars Hollow on the television series "Gilmore Girls," known for being Lorelai Gilmore’s close friend and neighbor.
-
E.
Myrna Fahey
Myrna Fahey was an American actress known for her film and television roles in the 1950s and 1960s, often appearing in comedies and dramas.
- 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_69f71f05b3e08190be0d4e0ad2bfb2d1 |
completed | May 3, 2026, 10:10 a.m. |
| NEDg | Description generation | batch_69f71fad1494819083484407dac16a7f |
completed | May 3, 2026, 10:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7205e52108190a5d3a1f50addb0f3 |
completed | May 3, 2026, 10:15 a.m. |
Created at: April 8, 2026, 9:45 p.m.