Triple
T30997017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Anaïs |
E789831
|
entity |
| Predicate | controlsSetting |
P178051
|
FINISHED |
| Object | high‑class Parisian brothel |
—
|
LITERAL 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: high‑class Parisian brothel | Statement: [Madame Anaïs, controlsSetting, high‑class Parisian brothel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlsSetting Context triple: [Madame Anaïs, controlsSetting, high‑class Parisian brothel]
-
A.
settingOfControl
chosen
Indicates that one entity is the context or environment in which another entity exercises control or governance.
-
B.
settingControlled
Indicates that one entity regulates, adjusts, or determines the configuration or parameters of another entity.
-
C.
exportControl
Indicates that an entity is subject to rules or restrictions governing the transfer or export of goods, services, or information across borders.
-
D.
controlParameter
Indicates that one entity functions as a parameter that governs, tunes, or constrains the behavior or operation of another entity.
-
E.
coversSetting
Indicates that one entity includes or addresses a particular setting or context within its scope.
- F. None of above.
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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd864235b481908738dbb69556bc62 |
completed | May 8, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69fd8373b6bc819091c554f29ee17fec |
completed | May 8, 2026, 6:32 a.m. |
Created at: April 29, 2026, 8:56 p.m.