Triple
T9674275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitra Production Hall by Álvaro Siza |
E234106
|
entity |
| Predicate | proportionTreatment |
P79134
|
FINISHED |
| Object | precise and measured |
—
|
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: precise and measured | Statement: [Vitra Production Hall by Álvaro Siza, proportionTreatment, precise and measured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proportionTreatment Context triple: [Vitra Production Hall by Álvaro Siza, proportionTreatment, precise and measured]
-
A.
hasProportion
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
B.
officialProportion
Indicates the proportion or percentage of something as formally defined or reported by an official source or authority.
-
C.
isProportionalityFactorIn
Indicates that one quantity serves as the proportionality factor (constant of proportionality) in a specified proportional relationship or equation.
-
D.
treatmentLevel
chosen
Indicates the degree or intensity of a treatment applied or received in a given context.
-
E.
hasProportionSystem
Indicates that one entity possesses or is characterized by a particular system for managing or defining proportions or ratios.
- 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6d6dd48190a77c486337a58cb6 |
completed | April 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:15 p.m.