Triple
T19955274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HUN |
E479664
|
entity |
| Predicate | hasSameStringAs |
P58927
|
FINISHED |
| Object | ISO 3166-1 alpha-3 code for Hungary |
—
|
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: ISO 3166-1 alpha-3 code for Hungary | Statement: [HUN, hasSameStringAs, ISO 3166-1 alpha-3 code for Hungary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSameStringAs Context triple: [HUN, hasSameStringAs, ISO 3166-1 alpha-3 code for Hungary]
-
A.
isSameSymbolAs
chosen
Indicates that two entities represent the identical symbol or sign, regardless of their specific instances or contexts.
-
B.
sameMatchAs
Indicates that two entities are considered equivalent or represent the same underlying match or correspondence in a given context.
-
C.
hasEqualRepresentationFrom
Indicates that two or more sources, groups, or categories contribute or are represented in equal proportion within a given context.
-
D.
hasCommonStringCount
Indicates that two entities share a specified number of identical string values in common.
-
E.
sameClassAs
Indicates that two entities belong to the same class or category within a given classification system.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65aefd9488190b8cdfa8543db8d31 |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.