Triple
T14048253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belleau, Aisne |
E338015
|
entity |
| Predicate | hasNearbyMemorialType |
P7960
|
FINISHED |
| Object | military cemetery and memorial complex |
—
|
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: military cemetery and memorial complex | Statement: [Belleau, Aisne, hasNearbyMemorialType, military cemetery and memorial complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyMemorialType Context triple: [Belleau, Aisne, hasNearbyMemorialType, military cemetery and memorial complex]
-
A.
hasAdjacentMemorial
Indicates that one memorial is located directly next to or in close proximity to another memorial.
-
B.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
C.
hasGraveOrMemorialOf
Indicates that a location or object serves as the grave or memorial site dedicated to a particular person or entity.
-
D.
memorialType
chosen
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
E.
hasMemorialContext
Indicates that something is related to, associated with, or situated within the context of a memorial or commemorative setting.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.