Triple
T33469379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of the Lithuanian SSR |
E857143
|
entity |
| Predicate | whiteStripeHeight |
P177042
|
FINISHED |
| Object | one-twentieth of flag height |
—
|
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: one-twentieth of flag height | Statement: [Flag of the Lithuanian SSR, whiteStripeHeight, one-twentieth of flag height]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: whiteStripeHeight Context triple: [Flag of the Lithuanian SSR, whiteStripeHeight, one-twentieth of flag height]
-
A.
whiteStripePosition
Indicates the relative location or alignment of a white stripe within or on an object.
-
B.
yellowStripeWidthRatio
Indicates the proportional width of a yellow stripe relative to a reference dimension (such as the total width or height of the object it appears on).
-
C.
sideRatioWhiteStripe
Indicates the proportional relationship between the width of the white stripe and another reference dimension on the side of an object or pattern.
-
D.
carpetStripeWidth
Indicates the width measurement of a stripe pattern on a carpet in the described context.
-
E.
topStripeWidth
Indicates the width measurement of the topmost stripe in a striped object or pattern.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f85bfba48190aba95b40642a8ca7 |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f814fcf48190ae4504154d1b2c05 |
completed | May 3, 2026, 7:24 a.m. |
Created at: May 1, 2026, 1:37 a.m.