Triple
T8778765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of French Polynesia |
E208668
|
entity |
| Predicate | stripeProportion |
P16308
|
FINISHED |
| Object | 1:2:1 |
—
|
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: 1:2:1 | Statement: [Flag of French Polynesia, stripeProportion, 1:2:1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stripeProportion Context triple: [Flag of French Polynesia, stripeProportion, 1:2:1]
-
A.
stripePlacement
Indicates the relative position or arrangement of a stripe on or across an object or surface.
-
B.
hasProportion
chosen
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
C.
redStripeProportion
Indicates the proportion of an object’s area or length that is occupied by a red stripe.
-
D.
blueStripeProportion
Indicates the proportion of an entity’s surface or area that is covered by a blue stripe relative to its total extent.
-
E.
officialProportion
Indicates the proportion or percentage of something as formally defined or reported by an official source or authority.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f531bd481909d877dadf9b6e9fb |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.