Triple
T1029036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafael Casanova |
E22206
|
entity |
| Predicate | roleDuringConflict |
P6060
|
FINISHED |
| Object | civil and military leader in Barcelona |
—
|
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: civil and military leader in Barcelona | Statement: [Rafael Casanova, roleDuringConflict, civil and military leader in Barcelona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringConflict Context triple: [Rafael Casanova, roleDuringConflict, civil and military leader in Barcelona]
-
A.
roleDuringConquest
Indicates the specific function, position, or capacity an entity held in relation to a particular conquest event.
-
B.
conflictRole
chosen
Indicates that an entity plays a specific role or position within a conflict or dispute between parties.
-
C.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
D.
worldWarIIRole
Indicates the specific role, position, or function an entity had in relation to World War II.
-
E.
role
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.