Triple
T7975997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ave Maria, Florida |
E185446
|
entity |
| Predicate | hasBuildingHeightFeature |
P30757
|
FINISHED |
| Object | prominent church with large facade and sculpture |
—
|
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: prominent church with large facade and sculpture | Statement: [Ave Maria, Florida, hasBuildingHeightFeature, prominent church with large facade and sculpture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBuildingHeightFeature Context triple: [Ave Maria, Florida, hasBuildingHeightFeature, prominent church with large facade and sculpture]
-
A.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
-
B.
buildingHeightCharacteristic
Indicates the specific height-related property or measurement that characterizes a building.
-
C.
buildingHeightContext
chosen
Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
-
D.
buildingHeight
Indicates the vertical extent or height measurement of a building.
-
E.
hasTowerHeight
Indicates that an entity (such as a tower or structure) has a specific height 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf56f688190902b95afe42635ec |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:14 p.m.