Triple
T5796552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady with a Unicorn |
E128520
|
entity |
| Predicate | sitterStatus |
P66579
|
FINISHED |
| Object | unidentified woman |
—
|
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: unidentified woman | Statement: [Lady with a Unicorn, sitterStatus, unidentified woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sitterStatus Context triple: [Lady with a Unicorn, sitterStatus, unidentified woman]
-
A.
sitter
Indicates that one entity is serving as a caretaker or guardian, typically watching over or looking after another entity.
-
B.
sitterNationality
Indicates the national identity or citizenship of the person who is sitting for a portrait or being depicted.
-
C.
sitterBirthPlace
Indicates the location where the person serving as the sitter was born.
-
D.
seeStatus
Indicates that one entity observes or becomes aware of the current state or condition of another entity or process.
-
E.
companionshipStatus
Indicates the current state or condition of a relationship of companionship between two or more entities.
- F. None of above. chosen
Provenance (4 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c02b10def8819080859bc6505405ed |
completed | March 22, 2026, 5:46 p.m. |
Created at: March 22, 2026, 3:51 p.m.