Triple
T27921201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joint Inspection Unit |
E706206
|
entity |
| Predicate | numberOfInspectors |
P199263
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Joint Inspection Unit, numberOfInspectors, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInspectors Context triple: [Joint Inspection Unit, numberOfInspectors, 11]
-
A.
numberOfInspectorsCreated
Indicates the total count of inspectors that have been created in the given context or system.
-
B.
usesInspectors
Indicates that one entity employs or relies on inspectors to examine, verify, or assess another entity or its activities.
-
C.
numberOfOfficials
Indicates the total count of officials associated with a given entity or context.
-
D.
numberOfCommissioners
Indicates the specific count of commissioners associated with a given entity or context.
-
E.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
- 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_69ef96b6cc808190aab19fb18b235f4b |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ff29d831b881908d485609e0fc1d0b |
completed | May 9, 2026, 12:34 p.m. |
| PD | Predicate disambiguation | batch_69ff28f9f9e4819087f3402735de66c7 |
completed | May 9, 2026, 12:30 p.m. |
| PDg | Predicate description generation | batch_69ff29d77f48819085304ed5e92eb906 |
completed | May 9, 2026, 12:34 p.m. |
Created at: April 27, 2026, 6:57 p.m.