Triple
T12870595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thanbyuzayat |
E307838
|
entity |
| Predicate | warCemeteryBurialsApproximate |
P95901
|
FINISHED |
| Object | over 3000 Allied servicemen |
—
|
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: over 3000 Allied servicemen | Statement: [Thanbyuzayat, warCemeteryBurialsApproximate, over 3000 Allied servicemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warCemeteryBurialsApproximate Context triple: [Thanbyuzayat, warCemeteryBurialsApproximate, over 3000 Allied servicemen]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
hasBurialsFromConflict
Indicates that the subject location or site contains burials that originated as a result of a specific conflict or violent event.
-
C.
hasWarGravesMaintainedBy
Indicates that one entity contains war graves whose upkeep and preservation are carried out by another entity.
-
D.
numberOfInterred
chosen
Indicates the total count of individuals who are buried or interred at a given site or within a specified context.
-
E.
cemeteryBurialsSince
Indicates the number of burials that have occurred in a cemetery from a specified point in time onward.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.