Triple
T22690661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vitrakvi |
E561039
|
entity |
| Predicate | hasFirstApprovalYear |
P62976
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [Vitrakvi, hasFirstApprovalYear, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstApprovalYear Context triple: [Vitrakvi, hasFirstApprovalYear, 2018]
-
A.
wasFirstApprovedIn
Indicates the time or context in which something (such as a proposal, product, or document) received its initial official approval.
-
B.
yearApproved
chosen
Indicates the specific year in which something (such as a proposal, product, or decision) was formally approved.
-
C.
hasFirstProofYear
Indicates the year in which something was first proven or formally demonstrated to be true.
-
D.
hasFirstCohortYear
Indicates the year in which the first cohort associated with an entity began or was established.
-
E.
regulatoryApprovalYear
Indicates the calendar year in which an official regulatory body granted approval for the referenced item, action, or 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789a1fd08190bce5fa0babe695d3 |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.