Triple
T13147957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amulet |
E312388
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Sarah Angliss
Sarah Angliss is a British composer, multi-instrumentalist, and sound artist known for blending electronics, robotics, and early music influences in her experimental works.
|
E1126242
|
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: Sarah Angliss | Statement: [Amulet, musicBy, Sarah Angliss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Angliss Context triple: [Amulet, musicBy, Sarah Angliss]
-
A.
Elizabeth Inglis
Elizabeth Inglis was a British actress best known for her roles in classic films such as "The Letter" and "The 39 Steps."
-
B.
Helen Dawes
Helen Dawes is a key supporting character in the period drama film "Albert Nobbs," involved in the emotional and social complexities surrounding the title character's secret life.
-
C.
Elizabeth Alington
Elizabeth Alington was a British aristocrat and the wife of Conservative politician and former UK Prime Minister Alec Douglas-Home.
-
D.
Anne Sutherland
Anne Sutherland is a Scottish operatic soprano renowned for her powerful voice and interpretations of bel canto repertoire.
-
E.
Margaret Johnston
Margaret Johnston was a British actress known for her work on stage and in films during the mid-20th century.
- 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: Sarah Angliss Triple: [Amulet, musicBy, Sarah Angliss]
Generated description
Sarah Angliss is a British composer, multi-instrumentalist, and sound artist known for blending electronics, robotics, and early music influences in her experimental works.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Angliss Target entity description: Sarah Angliss is a British composer, multi-instrumentalist, and sound artist known for blending electronics, robotics, and early music influences in her experimental works.
-
A.
Elizabeth Inglis
Elizabeth Inglis was a British actress best known for her roles in classic films such as "The Letter" and "The 39 Steps."
-
B.
Helen Dawes
Helen Dawes is a key supporting character in the period drama film "Albert Nobbs," involved in the emotional and social complexities surrounding the title character's secret life.
-
C.
Elizabeth Alington
Elizabeth Alington was a British aristocrat and the wife of Conservative politician and former UK Prime Minister Alec Douglas-Home.
-
D.
Anne Sutherland
Anne Sutherland is a Scottish operatic soprano renowned for her powerful voice and interpretations of bel canto repertoire.
-
E.
Margaret Johnston
Margaret Johnston was a British actress known for her work on stage and in films during the mid-20th century.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98bd0f5b08190ab700c5de1c8e138 |
completed | April 10, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b366470819093a74828e2a85116 |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6c2b7ec08190ba0b4a30cbb738e8 |
completed | May 8, 2026, 11:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6fff4f408190ac51668da19db284 |
completed | May 8, 2026, 11:21 p.m. |
Created at: April 9, 2026, 9:10 p.m.