Triple
T35026331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samrala |
E1010346
|
entity |
| Predicate | telephoneSystemCountry |
P182019
|
FINISHED |
| Object | India |
—
|
NE NERFINISHED |
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: India | Statement: [Samrala, telephoneSystemCountry, India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: telephoneSystemCountry Context triple: [Samrala, telephoneSystemCountry, India]
-
A.
telecommunicationsCountry
Indicates that a country is associated with or involved in telecommunications activities, services, or infrastructure.
-
B.
numericCountryCode
Indicates that a country is associated with a specific numeric code that uniquely identifies it.
-
C.
continentCode
Indicates the standardized code assigned to the continent with which an entity is associated.
-
D.
telephoneDialingCodeSystem
Indicates the telephone numbering or dialing code scheme used to place calls within or to a particular region, network, or service.
-
E.
mobileCountryCode
Indicates the numerical code that identifies the country associated with a mobile network or subscriber.
- 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_69f76dccf0108190af43b465d3750196 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7865578d48190bf90e470634fd97d |
completed | May 3, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f78575917481909a3defd6a4c366bd |
completed | May 3, 2026, 5:27 p.m. |
Created at: May 3, 2026, 4:01 p.m.