Triple
T11815155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Mary’s Cathedral, Sydney |
E280978
|
entity |
| Predicate | predecessorBuildingFireYear |
P101444
|
FINISHED |
| Object | 1865 |
—
|
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: 1865 | Statement: [St Mary’s Cathedral, Sydney, predecessorBuildingFireYear, 1865]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorBuildingFireYear Context triple: [St Mary’s Cathedral, Sydney, predecessorBuildingFireYear, 1865]
-
A.
predecessorBuildingDate
Indicates that one building’s construction date precedes that of another building in a temporal sequence.
-
B.
firstBuildingDestroyedByFire
Indicates that the first building in a given context was destroyed as a result of a fire.
-
C.
hasFormerBuilding
Indicates that an entity previously occupied or used a different building, which is identified as its former building.
-
D.
originYearOfPredecessor
Indicates the calendar year in which the predecessor entity first originated or was established.
-
E.
associatedBuildingDate
Indicates the date on which a particular building is formally linked or related to another entity or record.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a6574b7081908f7451d2bb233967 |
completed | April 10, 2026, 7:27 a.m. |
Created at: April 8, 2026, 9:42 p.m.