Triple
T20102148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buna |
E496570
|
entity |
| Predicate | hasWarCemeteriesNearby |
P42242
|
FINISHED |
| Object | Allied war graves (regional) |
—
|
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: Allied war graves (regional) | Statement: [Buna, hasWarCemeteriesNearby, Allied war graves (regional)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarCemeteriesNearby Context triple: [Buna, hasWarCemeteriesNearby, Allied war graves (regional)]
-
A.
hasNearbyMemorials
Indicates that one or more memorials are located in close physical proximity to the referenced entity.
-
B.
hasWarGravesMaintainedBy
Indicates that one entity contains war graves whose upkeep and preservation are carried out by another entity.
-
C.
hasNearbyCemetery
chosen
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with another entity.
-
D.
hasNearbyMilitaryHistorySite
Indicates that an entity is located close to a site of historical military significance, such as a battlefield, fort, or memorial.
-
E.
containsWarGravesOf
Indicates that a place or site includes burial locations or memorials for individuals who died in war.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66670a5b48190afe06c8a582bba3d |
completed | April 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e54cf788188190a46cc49c9ce7617f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:27 p.m.