Triple
T21270028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Wizna |
E524229
|
entity |
| Predicate | strengthOfDefenders |
P12310
|
FINISHED |
| Object | approximately 700 soldiers |
—
|
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: approximately 700 soldiers | Statement: [Battle of Wizna, strengthOfDefenders, approximately 700 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: strengthOfDefenders Context triple: [Battle of Wizna, strengthOfDefenders, approximately 700 soldiers]
-
A.
hasDefenderStrength
chosen
Indicates that an entity possesses a certain level or measure of defensive capability or protective power.
-
B.
attackerStrength
Indicates the level or magnitude of power, force, or capability possessed by the attacking entity in a given interaction or scenario.
-
C.
defenderBase
Indicates that one entity serves as the primary defensive location or stronghold associated with another entity.
-
D.
defenderIn
Indicates that an entity serves as a defensive agent or protector within a specified context, situation, or domain.
-
E.
defenderNotablyStiffArmed
Indicates that a defender forcefully extended their arm to fend off or block an opponent in a particularly notable or impactful way.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73651c9208190a87d45acd6fafaaa |
completed | April 21, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69e5f6161dac8190b06009cd180e3ff7 |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 16, 2026, 4:01 p.m.