Triple
T2657686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hello Mary Lou |
E54652
|
entity |
| Predicate | hasCoverVersionBy |
P11142
|
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: [Hello Mary Lou, hasCoverVersionBy, Queen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Context triple: [Hello Mary Lou, hasCoverVersionBy, Queen]
-
A.
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."
-
B.
Queen
A queen is a female monarch who serves as the sovereign head of state in a monarchy.
-
C.
Queen's
Queen's is a prestigious public research university located in Kingston, Ontario, Canada, known for its strong academic programs and historic campus.
-
D.
Queen B
Queen B is the nickname of Lil' Kim, an influential American rapper known for her provocative style, hardcore lyrics, and pioneering role for women in hip-hop.
-
E.
King
King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd94c61a08190bdf5e1caeff3e788 |
completed | March 7, 2026, 7:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98d535388190979a549dc2ce5f2f |
completed | March 10, 2026, 4:06 a.m. |
Created at: March 6, 2026, 9:53 p.m.