Triple
T2282390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COG |
E51308
|
entity |
| Predicate | hasCountryNumericCode |
P27637
|
FINISHED |
| Object | 178 |
—
|
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: 178 | Statement: [COG, hasCountryNumericCode, 178]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountryNumericCode Context triple: [COG, hasCountryNumericCode, 178]
-
A.
hasISO3166-1NumericCode
chosen
Indicates that an entity is associated with a specific ISO 3166-1 numeric country code.
-
B.
numericCode
Indicates that an entity is associated with a specific numerical identifier or classification code.
-
C.
FIPSCountryCode
Indicates that an entity is associated with a specific country as identified by its FIPS (Federal Information Processing Standards) country code.
-
D.
hasPostalCountryCode
Indicates that an entity is associated with a specific country code used for postal addressing or mail routing.
-
E.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21d6d748190980128c1bc5b9621 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdb9aa3c819088d0316c5269a1c2 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.