Triple
T65350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LERU |
E1301
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | LERU |
E1301
|
NE 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: LERU | Statement: [LERU, abbreviation, LERU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LERU Context triple: [LERU, abbreviation, LERU]
-
A.
LERU (former associate collaboration in some projects)
chosen
LERU (League of European Research Universities) is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education.
-
B.
El
El is the common nickname for Philadelphia’s elevated Market–Frankford rapid transit line operated by SEPTA.
-
C.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
D.
Gori
Gori is a city in central Georgia best known as the birthplace of Soviet leader Joseph Stalin.
-
E.
SU
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24ee6ba348190b00977285d74d8f5 |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2554da8848190a445b503d98769aa |
completed | Feb. 28, 2026, 2:39 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.