Triple
T23184160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modena Cathedral |
E579543
|
entity |
| Predicate | heightOfBellTower_m |
P151263
|
FINISHED |
| Object | 86 |
—
|
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: 86 | Statement: [Modena Cathedral, heightOfBellTower_m, 86]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heightOfBellTower_m Context triple: [Modena Cathedral, heightOfBellTower_m, 86]
-
A.
hasBellTower
Indicates that one entity (typically a building or structure) possesses or includes a bell tower as part of it.
-
B.
hasBellTowerHeightSignificance
Indicates that the height of a bell tower holds particular importance or relevance in a given context or relationship.
-
C.
hasMinaretHeightApprox
Indicates that an entity has a minaret whose height is approximately a specified value, allowing for some margin of imprecision.
-
D.
basilicaHeightApprox
Indicates that an entity is approximately a certain height, specifically in the context of a basilica or basilica-like structure.
-
E.
hasBellTowerLocation
Indicates the specific location where a bell tower is situated or attached relative to another structure or place.
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f717d248190b2736b0789981fb2 |
completed | April 29, 2026, 4:56 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:05 p.m.