Triple
T13307507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nysa |
E316972
|
entity |
| Predicate | uncertainStatus |
P62578
|
FINISHED |
| Object | exact real-world location disputed |
—
|
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: exact real-world location disputed | Statement: [Nysa, uncertainStatus, exact real-world location disputed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uncertainStatus Context triple: [Nysa, uncertainStatus, exact real-world location disputed]
-
A.
hasUncertainty
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
B.
hasUncertainNature
chosen
Indicates that the nature, status, or characteristics of the relationship or situation are not clearly defined, known, or determined.
-
C.
hasUncertainForm
Indicates that the form or structure of something is not clearly defined, fixed, or confidently known.
-
D.
hasUncertainNumber
Indicates that the associated quantity or count is not known precisely or cannot be determined with certainty.
-
E.
isUnstable
Indicates that the subject lacks stability or consistency, often changing, fluctuating, or failing to remain in a steady state.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.