Triple
T12925361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Mona Lisa |
E309229
|
entity |
| Predicate | appliedToWorkCreatedInYear |
P85809
|
FINISHED |
| Object | 1871 |
—
|
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: 1871 | Statement: [American Mona Lisa, appliedToWorkCreatedInYear, 1871]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToWorkCreatedInYear Context triple: [American Mona Lisa, appliedToWorkCreatedInYear, 1871]
-
A.
createdForWorkReleasedInYear
Indicates that something was created specifically for a work that was released in a particular year.
-
B.
appliesToWork
Indicates that something (such as a rule, policy, condition, or attribute) is relevant to, governs, or is in effect for a particular piece of work or work-related activity.
-
C.
appliedWork
Indicates that an entity has put effort, skill, or labor into performing or producing a particular work or task.
-
D.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
E.
workCompletionYear
chosen
Indicates the calendar year in which a particular work, project, or task was completed.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971eb17c88190bf523da897172a0c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.