Triple
T30091190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu ʿAbd Allah |
E764737
|
entity |
| Predicate | linkedPersonNationality |
P78054
|
FINISHED |
| Object | Persian |
—
|
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: Persian | Statement: [Abu ʿAbd Allah, linkedPersonNationality, Persian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedPersonNationality Context triple: [Abu ʿAbd Allah, linkedPersonNationality, Persian]
-
A.
associatedWithNationality
Indicates that one entity has a connection or affiliation with the nationality of another entity.
-
B.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
C.
nationalityOfPersonReferredTo
chosen
Indicates that one entity is the country or nationality associated with the person referenced by the other entity.
-
D.
userNationality
Indicates that a user has a specific national affiliation or citizenship.
-
E.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: April 29, 2026, 7:05 p.m.