Triple
T19506708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpine Training Center Aosta |
E488039
|
entity |
| Predicate | combatSpecialization |
P35675
|
FINISHED |
| Object | mountain infantry operations |
—
|
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: mountain infantry operations | Statement: [Alpine Training Center Aosta, combatSpecialization, mountain infantry operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: combatSpecialization Context triple: [Alpine Training Center Aosta, combatSpecialization, mountain infantry operations]
-
A.
weaponDiscipline
Indicates that an entity practices, adheres to, or is governed by a particular system, style, or code of weapon use or combat training.
-
B.
weaponProficiency
Indicates that an entity has the skill or qualification to effectively use a specified weapon.
-
C.
specialWeapon
Indicates that an entity is a weapon with unique, enhanced, or otherwise exceptional properties compared to standard weapons.
-
D.
methodOfCombat
chosen
Indicates the specific technique, style, or means by which an entity engages in combat or fighting.
-
E.
combatStyleAgainst
Indicates the specific way or method one entity uses to fight or engage in combat when facing another 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63511fc688190bd1474406060fa1b |
completed | April 20, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.