Triple
T125187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Bermuda |
E2530
|
entity |
| Predicate | frontDesignSameAsBack |
P4963
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Flag of Bermuda, frontDesignSameAsBack, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontDesignSameAsBack Context triple: [Flag of Bermuda, frontDesignSameAsBack, yes]
-
A.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
B.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
C.
badgeReverseDesign
Indicates the design or imagery that appears on the reverse (back) side of a badge.
-
D.
front
Indicates that one entity is located directly before or facing another entity along a primary viewing or movement direction.
-
E.
badgeObverseDesign
Indicates the design or imagery that appears on the front (obverse) side of a badge.
- 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_69a251b54ea88190b18281669f59b4c0 |
completed | Feb. 28, 2026, 2:23 a.m. |
| NER | Named-entity recognition | batch_69a2573e4e6481908252dfef2e34f46e |
completed | Feb. 28, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69a2564a54948190ba30bee858173b27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:27 a.m.