Triple
T2193132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RU11 (Research Universities 11) Japan |
E49908
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
RU11
RU11 is a consortium of eleven leading Japanese research-intensive universities that collaborate to promote advanced research and higher education.
|
E242605
|
NE FINISHED |
How this triple was built (4 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: RU11 | Statement: [RU11 (Research Universities 11) Japan, hasAbbreviation, RU11]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RU11 Context triple: [RU11 (Research Universities 11) Japan, hasAbbreviation, RU11]
-
A.
R11
R11 is the internal station code used by the New York City Subway for the Grand Central–42nd Street complex in Midtown Manhattan.
-
B.
R-11
R-11 is a Soviet short-range tactical ballistic missile that formed the basis for the later Scud missile family.
-
C.
RUI
RUI is the ticker symbol for the Russell 1000 Index, a major U.S. stock market index tracking the performance of the 1,000 largest publicly traded companies.
-
D.
RUVNN
RUVNN is the international port code assigned to the seaport of Vanino in Russia.
-
E.
RU-DA
RU-DA is the ISO 3166-2 regional code assigned to the Republic of Dagestan within the Russian Federation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: RU11 Triple: [RU11 (Research Universities 11) Japan, hasAbbreviation, RU11]
Generated description
RU11 is a consortium of eleven leading Japanese research-intensive universities that collaborate to promote advanced research and higher education.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RU11 Target entity description: RU11 is a consortium of eleven leading Japanese research-intensive universities that collaborate to promote advanced research and higher education.
-
A.
R11
R11 is the internal station code used by the New York City Subway for the Grand Central–42nd Street complex in Midtown Manhattan.
-
B.
R-11
R-11 is a Soviet short-range tactical ballistic missile that formed the basis for the later Scud missile family.
-
C.
RUI
RUI is the ticker symbol for the Russell 1000 Index, a major U.S. stock market index tracking the performance of the 1,000 largest publicly traded companies.
-
D.
RUVNN
RUVNN is the international port code assigned to the seaport of Vanino in Russia.
-
E.
RU-DA
RU-DA is the ISO 3166-2 regional code assigned to the Republic of Dagestan within the Russian Federation.
- F. None of above. chosen
Provenance (5 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf4a542881908aaaf4f0f85bc32c |
completed | March 7, 2026, 6:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5db283cc8190b75870cb2aabc5af |
completed | March 9, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69ae5e7b13108190bc3f4edbff3bdb24 |
completed | March 9, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5edfe80481908c3304c917c9065b |
completed | March 9, 2026, 5:47 a.m. |
Created at: March 4, 2026, 7:46 p.m.