Triple
T31410022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belfast City Cemetery |
E801234
|
entity |
| Predicate | hasReligiousSection |
P203299
|
FINISHED |
| Object | Protestant section |
—
|
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: Protestant section | Statement: [Belfast City Cemetery, hasReligiousSection, Protestant section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousSection Context triple: [Belfast City Cemetery, hasReligiousSection, Protestant section]
-
A.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
B.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
C.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
-
D.
hasReligiousSelection
Indicates that an entity is chosen, classified, or filtered based on religious criteria or affiliation.
-
E.
hasReligiousTheme
Indicates that something (such as a work, event, or object) centrally involves or expresses religious ideas, symbols, practices, or narratives.
- F. None of above. chosen
Provenance (4 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_69f348c0dd648190bf2fd7642f78eb06 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a014f7602988190b8f86cb431a9cf12 |
completed | May 11, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_6a014a70ea748190bd86fb9f218103ba |
completed | May 11, 2026, 3:18 a.m. |
| PDg | Predicate description generation | batch_6a014f751520819088cf1e697e0668ff |
completed | May 11, 2026, 3:39 a.m. |
Created at: April 30, 2026, 8:37 p.m.