Triple
T20449247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Monkey's Mask |
E501602
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Amanda Brown |
—
|
NE NERFINISHED |
How this triple was built (2 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: Amanda Brown | Statement: [The Monkey's Mask, musicBy, Amanda Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Brown Context triple: [The Monkey's Mask, musicBy, Amanda Brown]
-
A.
Amanda Brown
chosen
Amanda Brown is an Australian musician best known as the multi-instrumentalist and violinist for the indie rock band The Go-Betweens.
-
B.
Amanda Brown
Amanda Brown is an American author best known for writing the novel that inspired the hit film "Legally Blonde."
-
C.
Amanda Robinson
Amanda Robinson is the spouse of Jason Robinson.
-
D.
Amanda Young
Amanda Young is a central character in the Saw horror film franchise, known for being one of Jigsaw’s most prominent protégés and later a conflicted antagonist.
-
E.
Amanda Clayton
Amanda Clayton is an American actress best known for her role in the crime drama television series "City on a Hill."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfffae4819086c727f4143c2737 |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.