Triple
T16687679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorna Crozier |
E405507
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lorna Crozier |
—
|
NE NERFINISHED |
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: Lorna Crozier | Statement: [Lorna Crozier, name, Lorna Crozier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorna Crozier Context triple: [Lorna Crozier, name, Lorna Crozier]
-
A.
Lorna Crozier
chosen
Lorna Crozier is an acclaimed Canadian poet and educator known for her lyrical explorations of memory, landscape, and the human condition.
-
B.
Lorna Milne
Lorna Milne is a Scottish Liberal Democrat politician who served as a life peer in the House of Lords.
-
C.
Lorna Campbell
Lorna Campbell is a fictional British intelligence agent and key supporting character who assists the bumbling spy in the comedy film "Johnny English."
-
D.
Lorna Patterson
Lorna Patterson is an American actress best known for her comedic role as the singing stewardess in the classic parody film "Airplane!"
-
E.
Moira Davidson
Moira Davidson is a central character in Nevil Shute’s post-apocalyptic novel "On the Beach," known for her poignant transformation from a carefree socialite to a woman confronting the end of the world with courage and emotional depth.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ea75df481909a7ebb9b2a9d0afd |
completed | April 18, 2026, 12:52 p.m. |
Created at: April 10, 2026, 5:19 a.m.