Triple
T15246265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nana Coupeau |
E364389
|
entity |
| Predicate | hasLover |
P9994
|
FINISHED |
| Object | Count Muffat |
E347889
|
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: Count Muffat | Statement: [Nana Coupeau, hasLover, Count Muffat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Count Muffat Context triple: [Nana Coupeau, hasLover, Count Muffat]
-
A.
Count Muffat
chosen
Count Muffat is a wealthy, morally conflicted aristocrat in Émile Zola’s novel "Nana," whose obsession with the courtesan Nana leads to his social and financial ruin.
-
B.
Samuel Mauger
Samuel Mauger was an Australian politician and social reformer who served in the federal parliament in the early 20th century and was known for his advocacy of progressive labor and welfare policies.
-
C.
John Broughton
John Broughton was a Royal Navy officer best known for commanding the 44-gun frigate HMS Indefatigable during the late 18th century.
-
D.
Gil Caple
Gil Caple was an American saxophonist best known for his work with the influential Memphis soul and R&B instrumental group The Mar-Keys.
-
E.
Matthew Mott
Matthew Mott is an Australian cricket coach best known for leading successful limited-overs sides, including national teams in white-ball formats.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f4f9d48190b96a7e0c6993cd69 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd491cd881908bad9660af9b6b8f |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:13 a.m.