Triple
T15636040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | portraits of Marie Antoinette |
E375946
|
entity |
| Predicate | aimedToConvey |
P13485
|
FINISHED |
| Object | royal dignity |
—
|
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: royal dignity | Statement: [portraits of Marie Antoinette, aimedToConvey, royal dignity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimedToConvey Context triple: [portraits of Marie Antoinette, aimedToConvey, royal dignity]
-
A.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
B.
aimedToFacilitate
Indicates an action or arrangement that was intentionally designed to make another process, event, or outcome easier or more likely to occur.
-
C.
aimsToInform
Indicates an action whose purpose is to provide information or increase the knowledge of a target.
-
D.
aimOfEnglish
Indicates that something serves as the goal, purpose, or intended outcome within the context of English (e.g., English language, subject, or curriculum).
-
E.
intendedMessage
chosen
Indicates that one entity is the message or content that another entity aims or plans to communicate.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb8b4c48190b80fea6877483089 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.