Triple
T20993764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alan MacDonald |
E517090
|
entity |
| Predicate | workOn |
P30363
|
FINISHED |
| Object | The Queen |
—
|
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: The Queen | Statement: [Alan MacDonald, workOn, The Queen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Queen Context triple: [Alan MacDonald, workOn, The Queen]
-
A.
The Queen
The Queen is a 2006 British drama film directed by Stephen Frears that portrays the British royal family's response to the death of Princess Diana, featuring a celebrated score by Alexandre Desplat.
-
B.
The Queen
The Queen is the second studio album by American rapper Lil' Kim, known for its bold lyrics, high-profile collaborations, and influential role in late-1990s hip hop.
-
C.
The Queen
"The Queen" is one of the love poems by Chilean Nobel laureate Pablo Neruda, included in his influential 1924 collection *Twenty Love Poems and a Song of Despair*.
-
D.
The Queen
chosen
"The Queen" is a children's book by Alan MacDonald, best known as part of his humorous and educational stories often written for early readers.
-
E.
The Queen
The Queen is the regal ant monarch and mother of Princess Atta in Pixar's animated film "A Bug's Life."
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc1d829081908de889c542734393 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:50 p.m.