Triple
T11148859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Syria |
E263733
|
entity |
| Predicate | flagStripesOrder |
P77290
|
FINISHED |
| Object | red-white-black |
—
|
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: red-white-black | Statement: [Coat of arms of Syria, flagStripesOrder, red-white-black]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flagStripesOrder Context triple: [Coat of arms of Syria, flagStripesOrder, red-white-black]
-
A.
orderOfStripes
chosen
Indicates the sequential arrangement or pattern in which stripes appear relative to one another.
-
B.
flankedByStripes
Indicates that an entity is positioned between or bordered on both sides by stripe-like elements.
-
C.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
-
D.
orangeStripeRepresents
Indicates that an orange stripe symbolically stands for, denotes, or conveys the meaning of a particular concept, status, or entity.
-
E.
numberOfGoldStripes
Indicates the specific count of gold-colored stripes associated with an entity.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8701ea481908c86c2359f5dc957 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.