Triple
T198746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian flag |
E4054
|
entity |
| Predicate | hasPattern |
P8151
|
FINISHED |
| Object | Nordic cross |
—
|
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: Nordic cross | Statement: [Norwegian flag, hasPattern, Nordic cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPattern Context triple: [Norwegian flag, hasPattern, Nordic cross]
-
A.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
B.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
C.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
D.
hasParameter
Indicates that an entity is associated with a specific parameter that defines or constrains some aspect of its behavior, configuration, or characteristics.
-
E.
usesMatchesFrom
Indicates that one entity relies on or incorporates matches (e.g., pattern matches, rule matches, or result matches) produced by another entity or process.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25be47ea881909c296b30a0d47a65 |
completed | Feb. 28, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69a25b47481c8190add47c641c977bb9 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25be349588190aedde33d80682344 |
completed | Feb. 28, 2026, 3:07 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.