Triple
T6510370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Cross and Saint Joseph Cemetery |
E150111
|
entity |
| Predicate | hasReligiousRite |
P1186
|
FINISHED |
| Object | Roman Catholic funerary rites |
—
|
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: Roman Catholic funerary rites | Statement: [Holy Cross and Saint Joseph Cemetery, hasReligiousRite, Roman Catholic funerary rites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousRite Context triple: [Holy Cross and Saint Joseph Cemetery, hasReligiousRite, Roman Catholic funerary rites]
-
A.
hasRituals
Indicates that one entity performs, observes, or is associated with specific rituals in relation to another entity or context.
-
B.
hasRitual
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
C.
hasLifecycleRitual
Indicates that an entity is associated with a ritual or ceremonial practice marking a significant stage or transition in its lifecycle.
-
D.
hasRiteOrTradition
chosen
Indicates that an entity is associated with, practices, or observes a particular rite, ritual, or tradition.
-
E.
containsRite
Indicates that one entity includes or incorporates a specific rite as part of its structure, content, or practice.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f398f10819096342f3646cefcc2 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab98c78819081743e614df04e1d |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:43 p.m.