Triple
T12866960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riceyman Steps |
E307744
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Cassell |
E8434
|
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: Cassell | Statement: [Riceyman Steps, publisher, Cassell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cassell Context triple: [Riceyman Steps, publisher, Cassell]
-
A.
Cassell
chosen
Cassell is a British publishing company known for producing a wide range of books, including notable historical works and reference titles.
-
B.
Harcout
Harcourt is a small rural town in central Victoria, Australia, known historically for its apple orchards and granite quarries.
-
C.
Maunsel & Co.
Maunsel & Co. was an early 20th-century Irish publishing house known for issuing significant works of the Irish Literary Revival.
-
D.
Bodley Head
Bodley Head is a British publishing house known for its literary fiction, non-fiction, and classic works.
-
E.
Van Nostrand
Van Nostrand was an American publishing company known for producing influential academic and professional works in fields such as psychology, science, and engineering.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9708e0b788190b72a3057e271c227 |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb092b88190b159f1d79156cf86 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:38 p.m.