Triple
T30313551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | László Lukács |
E770992
|
entity |
| Predicate | spouseOfPersonWithOccupation |
P19181
|
FINISHED |
| Object | poet |
—
|
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: poet | Statement: [László Lukács, spouseOfPersonWithOccupation, poet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfPersonWithOccupation Context triple: [László Lukács, spouseOfPersonWithOccupation, poet]
-
A.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
B.
spouseOfRole
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
-
C.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
D.
spouseNotableFor
chosen
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
E.
spouseOfWork
Indicates that one person is the spouse of another specifically in the context of their workplace or professional environment.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcda3699948190adb57625bae08091 |
completed | May 7, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fd16d08190b0aca6e19a632e99 |
completed | May 7, 2026, 6:25 p.m. |
Created at: April 29, 2026, 7:51 p.m.