Triple
T6684425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afonso de Paiva |
E152064
|
entity |
| Predicate | searchObjective |
P34994
|
FINISHED |
| Object | locating the Christian kingdom of Prester John |
—
|
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: locating the Christian kingdom of Prester John | Statement: [Afonso de Paiva, searchObjective, locating the Christian kingdom of Prester John]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: searchObjective Context triple: [Afonso de Paiva, searchObjective, locating the Christian kingdom of Prester John]
-
A.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
B.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
C.
soughtTo
chosen
Indicates that one entity attempted or intended to obtain, achieve, or bring about another entity or outcome.
-
D.
goalDescription
Indicates that an entity expresses, specifies, or provides a textual description of a goal or intended outcome associated with another entity or activity.
-
E.
trainingObjective
Indicates the goal or target outcome that a training process is designed to achieve.
- 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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.