Triple
T16797942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Mary’s Basilica (Kraków) |
E408281
|
entity |
| Predicate | altarpieceMaterial |
P1272
|
FINISHED |
| Object | carved wood |
—
|
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: carved wood | Statement: [St. Mary’s Basilica (Kraków), altarpieceMaterial, carved wood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: altarpieceMaterial Context triple: [St. Mary’s Basilica (Kraków), altarpieceMaterial, carved wood]
-
A.
mainAltarMaterial
Indicates the material from which the main altar is made.
-
B.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
hasMainAltarpiece
Indicates that an entity (typically a religious building or space) possesses a specific artwork or structure serving as its principal altarpiece.
-
D.
hasAltarpieceWidth
Indicates the measured horizontal dimension (width) of an altarpiece.
-
E.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2ab08e8819097072a23c4a62392 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.