Triple
T24444140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diana Mosley |
E616353
|
entity |
| Predicate | witnessAtWedding |
P76666
|
FINISHED |
| Object | Adolf Hitler |
—
|
NE NERFINISHED |
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: Adolf Hitler | Statement: [Diana Mosley, witnessAtWedding, Adolf Hitler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: witnessAtWedding Context triple: [Diana Mosley, witnessAtWedding, Adolf Hitler]
-
A.
associatedWithWeddingOf
Indicates a relationship where something is connected or related to the wedding event of specific individuals.
-
B.
guestAtWedding
chosen
Indicates that a person is attending or has attended a particular wedding as a guest.
-
C.
guardianAfterElopement
Indicates that one entity serves as the legal or protective guardian of another entity following an elopement event.
-
D.
hasWeddingSceneWith
Indicates that two entities appear together in a wedding scene within the same context or work.
-
E.
bride
Indicates that an entity is a woman who is getting married or has just been married in relation to a wedding event or spouse.
- 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_69e2d7edca608190aafefc8877a1b4da |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29851e6cc8190a8f160cbed4e9ab0 |
completed | April 29, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.