Triple
T37821850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SUN COUNTRY |
E942938
|
entity |
| Predicate | operatorCountryCode |
P161773
|
FINISHED |
| Object | US |
E391583
|
NE 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: US | Statement: [SUN COUNTRY, operatorCountryCode, US]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorCountryCode Context triple: [SUN COUNTRY, operatorCountryCode, US]
-
A.
telephoneSystemCountry
Indicates that a telephone system operates within, or is associated with, a specific country.
-
B.
providerCountry
Indicates the country that serves as the source or origin of the provider in the relationship.
-
C.
mobileCountryCode
chosen
Indicates the numerical code that identifies the country associated with a mobile network or subscriber.
-
D.
telecommunicationsCountry
Indicates that a country is associated with or involved in telecommunications activities, services, or infrastructure.
-
E.
operatorCountrySection
Indicates that an operator is associated with, based in, or responsible for a specific country or country-defined section.
- F. None of above.
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_69f76ee987588190906506e759be5db3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0314e613f88190b5dbf89b9c4203c6 |
completed | May 12, 2026, 11:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40fb75363c8190b545165a40ae0c1a |
completed | June 28, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_6a0314699c1c8190b2a80dc4015e7890 |
completed | May 12, 2026, 11:52 a.m. |
Created at: May 3, 2026, 4:19 p.m.