Triple
T9455372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conference of European Regional Legislative Assemblies |
E228001
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CALRE
CALRE is a European organization that brings together regional legislative assemblies to promote cooperation, democratic participation, and representation within the European Union.
|
E801003
|
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: CALRE | Statement: [Conference of European Regional Legislative Assemblies, abbreviation, CALRE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CALRE Context triple: [Conference of European Regional Legislative Assemblies, abbreviation, CALRE]
-
A.
CAL
CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
-
B.
CAL
CAL is the station code for California station on the Green Line transit system.
-
C.
CAL
CAL was the stock ticker symbol for Continental Airlines, a major U.S. airline that later merged with United Airlines.
-
D.
Cal
Cal is the commonly used short name for the University of California, Berkeley and its associated athletic programs.
-
E.
Cal
Cal is the nickname and given name of Cal McNair, the American businessman and principal owner of the NFL’s Houston Texans.
- 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: CALRE Triple: [Conference of European Regional Legislative Assemblies, abbreviation, CALRE]
Generated description
CALRE is a European organization that brings together regional legislative assemblies to promote cooperation, democratic participation, and representation within the European Union.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CALRE Target entity description: CALRE is a European organization that brings together regional legislative assemblies to promote cooperation, democratic participation, and representation within the European Union.
-
A.
CAL
CAL is the ICAO airline designator used to identify China Airlines in international aviation operations.
-
B.
CAL
CAL is the station code for California station on the Green Line transit system.
-
C.
CAL
CAL was the stock ticker symbol for Continental Airlines, a major U.S. airline that later merged with United Airlines.
-
D.
Cal
Cal is the commonly used short name for the University of California, Berkeley and its associated athletic programs.
-
E.
Cal
Cal is the nickname and given name of Cal McNair, the American businessman and principal owner of the NFL’s Houston Texans.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f8e2c388190a4c5ee6e6d5f2585 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122849fec81908a8e7363d6bab4ed |
completed | April 4, 2026, 2:39 p.m. |
| NEDg | Description generation | batch_69d123f710988190a876fab3a1e226d3 |
completed | April 4, 2026, 2:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1252cd7508190a7d11fce51960290 |
completed | April 4, 2026, 2:50 p.m. |
Created at: March 30, 2026, 7:52 p.m.