Triple
T15925247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kosovo Specialist Chambers |
E386189
|
entity |
| Predicate | hasWitnessProtectionMeasures |
P120576
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kosovo Specialist Chambers, hasWitnessProtectionMeasures, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWitnessProtectionMeasures Context triple: [Kosovo Specialist Chambers, hasWitnessProtectionMeasures, yes]
-
A.
hasProtectionPurpose
Indicates that something is intended or designed to serve a protective function or goal.
-
B.
safeguardingMeasuresInclude
Indicates that certain specific protective or security measures are contained within, or form part of, a broader set of safeguarding measures.
-
C.
isProtectedFor
Indicates that one entity is safeguarded or preserved specifically for the benefit, use, or rights of another entity.
-
D.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
E.
providesProtectionIn
Indicates that one entity offers protection or safeguarding to another entity within a specified context, location, or situation.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e172b48b308190bc430b2308cbc75b |
completed | April 16, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e142cf5c548190a931f7b58144cd31 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e172b213e481909ee0c05e16229a26 |
completed | April 16, 2026, 11:37 p.m. |
Created at: April 10, 2026, 4:52 a.m.