Triple
T24582515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of Santa Rosa de Viterbo |
E608289
|
entity |
| Predicate | hasBellTowerCharacteristic |
P132657
|
FINISHED |
| Object | noticeably inclined from vertical |
—
|
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: noticeably inclined from vertical | Statement: [Temple of Santa Rosa de Viterbo, hasBellTowerCharacteristic, noticeably inclined from vertical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBellTowerCharacteristic Context triple: [Temple of Santa Rosa de Viterbo, hasBellTowerCharacteristic, noticeably inclined from vertical]
-
A.
bellTowerCharacteristic
chosen
Indicates that a specified characteristic or feature is associated with a bell tower.
-
B.
hasBellTower
Indicates that one entity (typically a building or structure) possesses or includes a bell tower as part of it.
-
C.
hasBellChamber
Indicates that an entity possesses or includes a bell chamber as one of its structural or functional components.
-
D.
hasBellTowerLocation
Indicates the specific location where a bell tower is situated or attached relative to another structure or place.
-
E.
hasBellWeight
Indicates that an entity (typically a bell) has a specific weight value associated with it.
- 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_69e2c4ce89248190ad99e18f0638dfbb |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a983a4408190acdf29ccd52be9d4 |
completed | April 30, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f2a6c1f07081908edf0b521767e79b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:29 a.m.