Triple
T8006915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commonwealth Legal Education Association |
E186384
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
CLEA
CLEA is an international organization that promotes and supports legal education and law teaching across Commonwealth countries.
|
E701758
|
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: CLEA | Statement: [Commonwealth Legal Education Association, abbreviation, CLEA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLEA Context triple: [Commonwealth Legal Education Association, abbreviation, CLEA]
-
A.
CLEO
CLEO is a major international scientific conference focused on lasers, electro-optics, and photonic technologies.
-
B.
Cleva
"Cleva" is a soulful neo-soul track by Erykah Badu from her acclaimed 2000 album "Mama’s Gun."
-
C.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
D.
Cleo
Cleo is the indigenous live-in housekeeper and emotional center of Alfonso Cuarón’s film "Roma," whose personal struggles unfold against the backdrop of 1970s Mexico City.
-
E.
Cleo
Cleo is a key supporting character in the musical "The Most Happy Fella," often portrayed as a lively, comedic waitress and confidante.
- 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: CLEA Triple: [Commonwealth Legal Education Association, abbreviation, CLEA]
Generated description
CLEA is an international organization that promotes and supports legal education and law teaching across Commonwealth countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CLEA Target entity description: CLEA is an international organization that promotes and supports legal education and law teaching across Commonwealth countries.
-
A.
CLEO
CLEO is a major international scientific conference focused on lasers, electro-optics, and photonic technologies.
-
B.
Cleva
"Cleva" is a soulful neo-soul track by Erykah Badu from her acclaimed 2000 album "Mama’s Gun."
-
C.
Clevsin
Clevsin is the ancient Etruscan name for the Italian town of Chiusi, a significant center of Etruscan civilization in central Italy.
-
D.
Cleo
Cleo is the indigenous live-in housekeeper and emotional center of Alfonso Cuarón’s film "Roma," whose personal struggles unfold against the backdrop of 1970s Mexico City.
-
E.
Cleo
Cleo is a key supporting character in the musical "The Most Happy Fella," often portrayed as a lively, comedic waitress and confidante.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3cf8a6048190970685a83fd2f59d |
completed | March 31, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe12c068c8190a6ea7e924a7748c6 |
completed | March 31, 2026, 2:58 p.m. |
| NEDg | Description generation | batch_69cbe442999881909544802bb9a91cd5 |
completed | March 31, 2026, 3:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc09c676148190964d4947310ec16a |
completed | March 31, 2026, 5:52 p.m. |
Created at: March 30, 2026, 5:18 p.m.