Triple
T23962453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Rubinstein |
E603963
|
entity |
| Predicate | knownAsPioneerIn |
P2809
|
FINISHED |
| Object | modern cosmetics marketing |
—
|
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: modern cosmetics marketing | Statement: [Madame Rubinstein, knownAsPioneerIn, modern cosmetics marketing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownAsPioneerIn Context triple: [Madame Rubinstein, knownAsPioneerIn, modern cosmetics marketing]
-
A.
pioneerOf
chosen
Indicates that an entity was among the first to develop, introduce, or significantly advance another entity, concept, or practice.
-
B.
pioneeringAspect
Indicates that something embodies an innovative, trailblazing, or first-of-its-kind quality within a particular domain or context.
-
C.
hasNotablePioneer
Indicates that an entity is associated with a person who played a pioneering or trailblazing role in its development, establishment, or early advancement.
-
D.
namedPersonNotableFor
Indicates that a person is especially known or recognized for a particular work, role, achievement, or characteristic.
-
E.
notableInventor
Indicates that the subject is a well-known or historically significant inventor of the object.
- 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_69e2954222288190a7323554d0cca8d7 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d0db90c88190adc18e9ee107281b |
completed | April 29, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:23 p.m.