Triple
T21950770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UniFE |
E542061
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | CRUI |
—
|
NE NERFINISHED |
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: CRUI | Statement: [UniFE, memberOf, CRUI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CRUI Context triple: [UniFE, memberOf, CRUI]
-
A.
CRUI
chosen
CRUI is the Conference of Italian University Rectors, a national association representing and coordinating the leadership of Italian universities.
-
B.
CRUE
CRUE is the main association representing Spanish universities, coordinating and promoting their interests in higher education and research.
-
C.
CRI
CRI is the three-letter ISO 3166-1 alpha-3 country code assigned to Costa Rica.
-
D.
CRI
CRI is a Kubernetes plugin interface that standardizes how container runtimes integrate with the Kubernetes kubelet to manage containers and pods.
-
E.
CRI
CRI is the National Rail station code for Cricklewood railway station in north-west London, England.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243bb9c88190a3774b9fa2af9871 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:58 p.m.