Triple
T21684690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Assembly complex |
E535198
|
entity |
| Predicate | geometricFeature |
P145444
|
FINISHED |
| Object | circular openings |
—
|
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: circular openings | Statement: [National Assembly complex, geometricFeature, circular openings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geometricFeature Context triple: [National Assembly complex, geometricFeature, circular openings]
-
A.
geometricFunction
Indicates a relationship where one entity serves as a geometric transformation or operation that, when applied, produces or modifies another geometric entity.
-
B.
geometricConfiguration
Indicates the specific spatial arrangement and relationships among parts or elements within a geometric structure.
-
C.
geometricSetting
Indicates the spatial or geometric context within which an object, relation, or event is defined or occurs.
-
D.
metricalFeature
Indicates a relationship where one entity specifies or characterizes a metrical property or pattern of another entity.
-
E.
geometricConsequence
Indicates that one geometric fact, configuration, or property logically follows from or is implied by another within a geometric context.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96ca668481909f53853c7a8ea811 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:44 p.m.