Triple
T937252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Leipzig |
E20223
|
entity |
| Predicate | numberOfCombatants |
P6153
|
FINISHED |
| Object | over 500000 |
—
|
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: over 500000 | Statement: [Battle of Leipzig, numberOfCombatants, over 500000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCombatants Context triple: [Battle of Leipzig, numberOfCombatants, over 500000]
-
A.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
-
B.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
C.
numberLaunchedInCombat
Indicates the quantity of times an entity has been launched or deployed specifically in combat operations.
-
D.
numberOfInvaders
Indicates the quantity of entities classified as invaders associated with a given subject or context.
-
E.
mainCombatant
Indicates that the subject is the primary participant or leading party in a conflict, battle, or combat situation involving the object.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3668a3c8190b0152166efa93ee1 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29c68f48190aecad10e351a99de |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.