Triple
T34264702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbey of Sainte-Geneviève |
E879132
|
entity |
| Predicate | buildingsTransformedInto |
P73483
|
FINISHED |
| Object | Panthéon, Paris |
—
|
NE NERFINISHED |
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: Panthéon, Paris | Statement: [Abbey of Sainte-Geneviève, buildingsTransformedInto, Panthéon, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingsTransformedInto Context triple: [Abbey of Sainte-Geneviève, buildingsTransformedInto, Panthéon, Paris]
-
A.
buildingConvertedTo
chosen
Indicates that one building has been transformed, repurposed, or adapted into another type or use of building.
-
B.
reconstructedBuilding
Indicates that a building has been rebuilt or restored after damage, destruction, or significant alteration.
-
C.
buildings
Indicates that one or more buildings are associated with, located at, or relevant to the referenced entity.
-
D.
eraOfManyBuildings
Indicates a time period during which many buildings were constructed or existed.
-
E.
rebuiltAsPermanentStructure
Indicates that something previously temporary or provisional has been reconstructed or replaced as a lasting, permanent structure.
- 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_69f349b4f5fc819094b441d18e95e5f1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:56 a.m.