Triple
T619492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Nicholas Anapausas Monastery |
E14479
|
entity |
| Predicate | buildingLevels |
P17185
|
FINISHED |
| Object | multiple storeys built vertically on the rock |
—
|
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: multiple storeys built vertically on the rock | Statement: [St. Nicholas Anapausas Monastery, buildingLevels, multiple storeys built vertically on the rock]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingLevels Context triple: [St. Nicholas Anapausas Monastery, buildingLevels, multiple storeys built vertically on the rock]
-
A.
buildingSection
Indicates a relationship where one entity is a specific section, part, or subdivision of a larger building.
-
B.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
C.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
D.
towerType
Indicates the specific kind or classification of a tower that an entity is associated with or represents.
-
E.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e270b448190beb677670443b5b6 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfe9bc081909a01b4b3b48f03b7 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.