Triple
T9082550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novy Urengoy |
E217668
|
entity |
| Predicate | hasSignificantCompanyPresence |
P19182
|
FINISHED |
| Object | Gazprom subsidiaries |
—
|
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: Gazprom subsidiaries | Statement: [Novy Urengoy, hasSignificantCompanyPresence, Gazprom subsidiaries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignificantCompanyPresence Context triple: [Novy Urengoy, hasSignificantCompanyPresence, Gazprom subsidiaries]
-
A.
hasCorporatePresence
Indicates that an organization maintains an official operational or business presence (such as offices, facilities, or legal registration) in a particular location or context.
-
B.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
C.
hasNotableCompany
chosen
Indicates that an entity is associated with or linked to a company that is considered notable or significant in some context.
-
D.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
-
E.
hasNumberOfCompanies
Indicates the quantitative relationship specifying how many companies are associated with 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc960a2760819084aab611eb1c43a9 |
completed | April 1, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:13 p.m.