Triple
T12565717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apostle of Brazil |
E295472
|
entity |
| Predicate | appliedToPersonRole |
P105463
|
FINISHED |
| Object | missionary |
—
|
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: missionary | Statement: [Apostle of Brazil, appliedToPersonRole, missionary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToPersonRole Context triple: [Apostle of Brazil, appliedToPersonRole, missionary]
-
A.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
-
B.
appliedDuringRole
Indicates that an action, method, or process was carried out specifically while an entity was serving in a particular role or position.
-
C.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
D.
hasOrganizationalRole
Indicates that an entity holds a specific role, position, or function within an organization.
-
E.
possibleRole
Indicates that an entity is capable of or eligible to serve in a particular role or function in a given context.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d9550af6d48190a40e349ed0424be3 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 8, 2026, 11:49 p.m.