Triple
T25478750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langemark German war cemetery |
E638505
|
entity |
| Predicate | nearbyCemeteries |
P41335
|
FINISHED |
| Object | Tyne Cot Commonwealth War Graves Cemetery |
—
|
NE NERFINISHED |
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: Tyne Cot Commonwealth War Graves Cemetery | Statement: [Langemark German war cemetery, nearbyCemeteries, Tyne Cot Commonwealth War Graves Cemetery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCemeteries Context triple: [Langemark German war cemetery, nearbyCemeteries, Tyne Cot Commonwealth War Graves Cemetery]
-
A.
nearbyCemetery
chosen
Indicates that one entity is located close to or in the immediate vicinity of a cemetery.
-
B.
nearbyTomb
Indicates that one entity is located close to or in the immediate vicinity of a tomb.
-
C.
hasNearbyCemetery
Indicates that one entity is located close to, or in the immediate vicinity of, a cemetery associated with another entity.
-
D.
hasCemetery
Indicates that one entity possesses, contains, or includes a cemetery associated with it.
-
E.
burialSiteNear
Indicates that the burial site of one entity is located geographically close to 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_69e75db9b964819096802dcf502e577e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 21, 2026, 2:27 p.m.