Triple
T22619643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UM |
E558239
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | LERU |
—
|
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: LERU | Statement: [UM, memberOf, LERU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LERU Context triple: [UM, memberOf, LERU]
-
A.
LERU
chosen
LERU is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education in Europe.
-
B.
ERU
ERU is the standard unit used to quantify emissions reductions achieved through Joint Implementation projects under the Kyoto Protocol.
-
C.
LER
LER is the vehicle registration code assigned to the German island municipality of Borkum.
-
D.
LER
LER is the National Rail station code for Leytonstone High Road railway station in London.
-
E.
LER
LER is the abbreviation for The Loyal Eddies, a group or organization likely centered around shared loyalty or fandom, often in a sports or community context.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e383b048190a432c540185916d0 |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 3 p.m.