Triple
T11167016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pounou |
E264184
|
entity |
| Predicate | maskFunction |
P87611
|
FINISHED |
| Object | representation of idealized female beauty |
—
|
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: representation of idealized female beauty | Statement: [Pounou, maskFunction, representation of idealized female beauty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maskFunction Context triple: [Pounou, maskFunction, representation of idealized female beauty]
-
A.
mayMask
Indicates that one entity is permitted or able to conceal, obscure, or hide another entity or its properties.
-
B.
maskPattern
chosen
Indicates a relationship where one entity serves as a masking template or pattern that determines which parts or aspects of another entity are revealed, hidden, or transformed.
-
C.
cryptFunction
Indicates a function or method that performs cryptographic processing, such as encrypting, decrypting, or otherwise transforming data using a cryptographic algorithm.
-
D.
metaFunction
Indicates that one function operates on, describes, or manipulates other functions or their behavior at a higher (meta) level.
-
E.
maskColor
Indicates the color attribute associated with a mask.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e88843cc81909e503f0921c6d297 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75cec26fc8190a5497d186306f935 |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:29 p.m.