Triple
T19396376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Dougan |
E485197
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Susan Dougan |
—
|
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: Susan Dougan | Statement: [Susan Dougan, name, Susan Dougan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Dougan Context triple: [Susan Dougan, name, Susan Dougan]
-
A.
Susan Dougan
chosen
Susan Dougan is a Vincentian public figure who serves as the Governor-General and de facto representative of the British monarch in Saint Vincent and the Grenadines.
-
B.
Lorna Crozier
Lorna Crozier is an acclaimed Canadian poet and educator known for her lyrical explorations of memory, landscape, and the human condition.
-
C.
Susan McMartin
Susan McMartin is an American television and film writer best known for her work on series such as "Mom" and "Two and a Half Men."
-
D.
Joanne Gordon
Joanne Gordon is a business writer and author known for profiling entrepreneurs and innovative companies, including in her book "Moonshot!: Game-Changing Strategies to Build Billion-Dollar Businesses."
-
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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62573f5788190a635b92121db2cf7 |
completed | April 20, 2026, 1:09 p.m. |
Created at: April 10, 2026, 1:36 p.m.