Triple
T11733686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emmanuelle Vaugier |
E278969
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mistresses |
E439126
|
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: Mistresses | Statement: [Emmanuelle Vaugier, notableWork, Mistresses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mistresses Context triple: [Emmanuelle Vaugier, notableWork, Mistresses]
-
A.
Mistresses
chosen
Mistresses is an American television drama series that follows the complicated romantic and personal lives of four female friends.
-
B.
Mistress and Maid
Mistress and Maid is a song featured on Paul McCartney’s 1993 album "Off the Ground."
-
C.
The Mistress
The Mistress is the later female incarnation of the Doctor’s longtime Time Lord nemesis the Master in the British science-fiction series Doctor Who.
-
D.
The Mistress
The Mistress is a collection of love poems by 17th-century English metaphysical poet Abraham Cowley, exploring themes of passion, desire, and romantic idealization.
-
E.
Mistress Quickly
Mistress Quickly is a comic, talkative hostess and recurring character in Shakespeare’s Henry IV plays and The Merry Wives of Windsor, known for her malapropisms and bustling presence in tavern scenes.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4daa7f48190896fc7653e9dd70b |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8406fe8881909722ecb040087e68 |
completed | April 27, 2026, 3:43 p.m. |
Created at: April 8, 2026, 9:41 p.m.