Triple
T13476569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of Toulouse |
E318265
|
entity |
| Predicate | hasMilitaryTactic |
P30685
|
FINISHED |
| Object | use of siege engines |
—
|
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: use of siege engines | Statement: [Siege of Toulouse, hasMilitaryTactic, use of siege engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryTactic Context triple: [Siege of Toulouse, hasMilitaryTactic, use of siege engines]
-
A.
militaryTacticsUsed
chosen
Indicates that specific military tactics are employed or applied in the context of a particular operation, conflict, or strategic situation.
-
B.
tacticalFeatureUsed
Indicates that a specific tactical feature, maneuver, or capability is employed or brought into play within a tactical situation or operation.
-
C.
hasPrimaryTactic
Indicates that an entity is associated with its main or most commonly used tactic or method of operation.
-
D.
militaryTacticsFaced
Indicates that an entity encountered or had to contend with specific military tactics employed by another entity.
-
E.
tacticsManualUsedBy
Indicates that a tactics manual is utilized or applied by a particular agent or entity.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2551b48190a074fd256791742d |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.