Triple
T23181110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radio Recorders, Hollywood |
E579460
|
entity |
| Predicate | usedByArtist |
P46218
|
FINISHED |
| Object | Queen |
E200825
|
NE FINISHED |
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: Queen | Statement: [Radio Recorders, Hollywood, usedByArtist, Queen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Context triple: [Radio Recorders, Hollywood, usedByArtist, Queen]
-
A.
Queen
A queen is a female monarch who serves as the sovereign head of state in a monarchy.
-
B.
Queen
The Queen in Andrew Lloyd Webber's "Cinderella" is a regal, often comedic royal figure who embodies the story's satirical take on traditional fairy-tale monarchy and social expectations.
-
C.
Queen
Queen is the intelligent, principled female protagonist of the 2019 romantic crime drama film "Queen & Slim."
-
D.
Queen
chosen
Queen is a legendary British rock band known for its theatrical style, powerful vocals by Freddie Mercury, and iconic hits like "Bohemian Rhapsody" and "We Will Rock You."
-
E.
Queen
"Queen" is a 2018 pop single by British singer-songwriter Jessie J that promotes self-acceptance and body positivity.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f6ebff48190ad1543051ca0239b |
completed | April 29, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c30b1bb248190acc8f31308f736bc |
completed | May 19, 2026, 9:43 a.m. |
Created at: April 17, 2026, 4:05 p.m.