Triple
T3492173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GS |
E73757
|
entity |
| Predicate | codeContext |
P19363
|
FINISHED |
| Object | country and territory identification |
—
|
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: country and territory identification | Statement: [GS, codeContext, country and territory identification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeContext Context triple: [GS, codeContext, country and territory identification]
-
A.
codeSpace
Indicates the namespace or contextual scope within which a piece of code, identifier, or programming element is defined and interpreted.
-
B.
hasCodeContext
chosen
Indicates that an entity is associated with or occurs within a particular programming or code-related context.
-
C.
scriptCode
Indicates that an entity is associated with a particular writing system or script, identified by a standardized script code.
-
D.
codeSection
Indicates a specific segment or subsection within a larger body of code that is distinguished for reference, organization, or analysis.
-
E.
codeExample
Indicates that one entity provides a snippet or sample of source code that illustrates how to use, implement, or demonstrate another 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbabd1708190b1ca4cbc87462b5b |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0b34908190b2bb5766a2231f7a |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.