Triple
T15924337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kosovo Protection Corps |
E386167
|
entity |
| Predicate | hasSizeAtPeak |
P4549
|
FINISHED |
| Object | approximately 5000 members |
—
|
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: approximately 5000 members | Statement: [Kosovo Protection Corps, hasSizeAtPeak, approximately 5000 members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSizeAtPeak Context triple: [Kosovo Protection Corps, hasSizeAtPeak, approximately 5000 members]
-
A.
hasPeakCount
Indicates the number of distinct peaks associated with an entity.
-
B.
hasPeak
Indicates that something possesses or contains a highest point, summit, or maximum value.
-
C.
memberCountAtPeak
chosen
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
D.
deploymentPeakNumber
Indicates the maximum number of deployments (or deployment instances) reached during a specified period or under given conditions.
-
E.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
- 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_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. |
Created at: April 10, 2026, 4:52 a.m.