Triple
T34643757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikas engine |
E889638
|
entity |
| Predicate | technologySourceCountry |
P126219
|
FINISHED |
| Object | France |
—
|
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: France | Statement: [Vikas engine, technologySourceCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologySourceCountry Context triple: [Vikas engine, technologySourceCountry, France]
-
A.
technologyOrigin
Indicates that one entity is the source, creator, or originating context of a particular technology associated with another entity.
-
B.
engineOriginCountry
chosen
Indicates the country where an engine was originally designed, manufactured, or first produced.
-
C.
homeworldOfTechnology
Indicates that a particular world or planet is the original place of origin or primary base for a given technology.
-
D.
organizationCountryOfOrigin
Indicates the country where an organization was originally founded or established.
-
E.
acquisitionCountry
Indicates the country in which the acquisition of an entity or asset took place.
- 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_69f349d825c88190bfc6170ac9281260 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 2:04 a.m.