Triple
T328707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German 4th Panzer Army |
E6576
|
entity |
| Predicate | garrisonDuringWar |
P11474
|
FINISHED |
| Object | various locations on Eastern Front |
—
|
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: various locations on Eastern Front | Statement: [German 4th Panzer Army, garrisonDuringWar, various locations on Eastern Front]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garrisonDuringWar Context triple: [German 4th Panzer Army, garrisonDuringWar, various locations on Eastern Front]
-
A.
garrisonLabel
Indicates the designation or identifying label assigned to a military garrison associated with an entity.
-
B.
garrisonDuringFormation
Indicates that a military unit is stationed in a specific garrison location during its period of formation or initial organization.
-
C.
enemyDuringWar
Indicates that one entity is an enemy of another specifically in the context of a particular war or armed conflict.
-
D.
seatDuringWar
Indicates that an entity holds or occupies a seat, position, or place during a time of war or armed conflict.
-
E.
countryOfGarrison
Indicates the country in which a military unit, base, or garrison is stationed or based.
- F. None of above. chosen
Provenance (4 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eaad37b0819085beda2a491da9a8 |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94aab1c8190b8654708c87eeb91 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea09a5e881908b313cb37409a4f9 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.