Triple
T7565309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notre-Dame-des-Neiges Cemetery |
E178897
|
entity |
| Predicate | interments |
P14555
|
FINISHED |
| Object | over 1 million burials |
—
|
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 1 million burials | Statement: [Notre-Dame-des-Neiges Cemetery, interments, over 1 million burials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interments Context triple: [Notre-Dame-des-Neiges Cemetery, interments, over 1 million burials]
-
A.
burials
Indicates that one entity is interred or laid to rest in a grave or burial site associated with another entity.
-
B.
hasBurialsFrom
Indicates that a location or site contains burials originating from a specified time period, culture, or source.
-
C.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
D.
hasBurialsOf
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
-
E.
burialBy
Indicates that one entity is responsible for burying or interring 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8fc6a408190abf363a29359e764 |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4dc485c819080da13e3b7f4f08f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:50 p.m.