Triple
T6288892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Trinidad and Tobago |
E140965
|
entity |
| Predicate | proportionWidth |
P70703
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Flag of Trinidad and Tobago, proportionWidth, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proportionWidth Context triple: [Flag of Trinidad and Tobago, proportionWidth, 5]
-
A.
proportionalTo
Indicates that one quantity varies in constant ratio to another, so changes in one are directly reflected by proportional changes in the other.
-
B.
isProportionalTo
Indicates that one quantity varies in constant ratio to another, so when one changes, the other changes by a fixed multiplicative factor.
-
C.
hasProportion
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
D.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
E.
officialProportion
Indicates the proportion or percentage of something as formally defined or reported by an official source or authority.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0641a6ecc8190a63be0e3f0344a3f |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c06284848c8190a0151ff3e8682889 |
completed | March 22, 2026, 9:43 p.m. |
Created at: March 22, 2026, 4:26 p.m.