Triple
T23990497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Raphaels |
E605049
|
entity |
| Predicate | hasReligiousBuildingRuins |
P916
|
FINISHED |
| Object | stone Roman Catholic church |
—
|
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: stone Roman Catholic church | Statement: [St. Raphaels, hasReligiousBuildingRuins, stone Roman Catholic church]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousBuildingRuins Context triple: [St. Raphaels, hasReligiousBuildingRuins, stone Roman Catholic church]
-
A.
hasMonasteryRuins
Indicates that an entity possesses or contains the remains or ruins of a former monastery.
-
B.
hasReligiousSite
chosen
Indicates that a location or entity possesses, contains, or is associated with a religious site such as a temple, church, mosque, shrine, or similar place of worship.
-
C.
formerReligiousBuilding
Indicates that a building previously served a religious function but no longer does so.
-
D.
hasStoneMonument
Indicates that one entity possesses, contains, or features a stone monument associated with it.
-
E.
usesAncientStructure
Indicates that one entity makes use of, incorporates, or relies on an ancient structure in its function, design, or activity.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38b37648190afb003cded3a7484 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:37 p.m.