Triple
T37562998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquis of Maranhão |
E933874
|
entity |
| Predicate | holderNationalityAtGrant |
P17302
|
FINISHED |
| Object | British |
—
|
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: British | Statement: [Marquis of Maranhão, holderNationalityAtGrant, British]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holderNationalityAtGrant Context triple: [Marquis of Maranhão, holderNationalityAtGrant, British]
-
A.
granteeNotableNationality
Indicates that the grantee has a notable or significant association with a particular nationality.
-
B.
ownerNationality
Indicates that the owner of an entity has the specified nationality.
-
C.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
D.
hasLaureateCitizenship
Indicates that a laureate holds or has held citizenship in a specified country or political entity.
-
E.
officeHolderNationality
chosen
Indicates that the nationality of an office holder is a specified country or nation.
- 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_69f76ecb4acc8190b53f96d0b013e415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba61dff5081909fec88a7aeb0c8a1 |
completed | May 6, 2026, 8:35 p.m. |
| PD | Predicate disambiguation | batch_69fba350e9a8819095893229d9643572 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.