Triple
T9537093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Arbour |
E230045
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Louise Arbour |
E230045
|
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: Louise Arbour | Statement: [Louise Arbour, name, Louise Arbour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louise Arbour Context triple: [Louise Arbour, name, Louise Arbour]
-
A.
Louise Arbour
chosen
Louise Arbour is a Canadian jurist and former UN High Commissioner for Human Rights known for her pioneering work in international criminal law and human rights advocacy.
-
B.
Louise L’Heureux
Louise L’Heureux was the wife of prominent Quebec premier and sovereigntist leader René Lévesque.
-
C.
John Annan
John Annan is a notable individual who shares the surname associated with prominent figures such as former UN Secretary-General Kofi Annan.
-
D.
Cyrus Vance
Cyrus Vance was an American lawyer and diplomat who served as U.S. Secretary of State under President Jimmy Carter.
-
E.
Michaëlle Jean
Michaëlle Jean is a Haitian-born Canadian journalist, stateswoman, and former Governor General of Canada who later served as Secretary-General of the Organisation internationale de la Francophonie.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98ce884c8190a8b3c2dc7c73c2c9 |
completed | April 1, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c4f1fc08190a1ad3d862717eef3 |
completed | April 4, 2026, 5:37 p.m. |
Created at: March 30, 2026, 8:01 p.m.