Triple
T28103167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kthi |
E710288
|
entity |
| Predicate | scriptPrimaryCountry |
P172129
|
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: [Kthi, scriptPrimaryCountry, India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptPrimaryCountry Context triple: [Kthi, scriptPrimaryCountry, India]
-
A.
primaryRouteCountry
Indicates the country that serves as the main or principal route location associated with the subject.
-
B.
primaryReferenceCountry
Indicates the main country that serves as the primary point of reference or association for the related entity.
-
C.
hasPrimaryNation
Indicates that one entity is designated as the main or principal nation associated with another entity.
-
D.
primaryUseCountry
Indicates the country in which something is primarily used or most commonly utilized.
-
E.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8de0b948190ae333e9cd99cbf6c |
completed | May 3, 2026, 1:46 a.m. |
Created at: April 27, 2026, 9:06 p.m.