Triple
T22824896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyotomi Hidenaga |
E565625
|
entity |
| Predicate | militarySkill |
P87507
|
FINISHED |
| Object | strategy |
—
|
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: strategy | Statement: [Toyotomi Hidenaga, militarySkill, strategy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militarySkill Context triple: [Toyotomi Hidenaga, militarySkill, strategy]
-
A.
militaryCharacteristic
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
B.
warfareCapability
Indicates the ability or capacity of an entity to engage in, conduct, or support acts of warfare.
-
C.
weaponProficiency
Indicates that an entity has the skill or qualification to effectively use a specified weapon.
-
D.
killsAt
Indicates that one entity causes the death of another entity at a specific time or event.
-
E.
hasMilitarySpeciality
chosen
Indicates that an entity possesses a specific military role, skill set, or area of professional expertise within the armed forces.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dd34a248190881f2bccdd9aedce |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:34 p.m.