Triple
T1699591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penguin Random House |
E36737
|
entity |
| Predicate | hasImprint |
P2763
|
FINISHED |
| Object | Knopf |
E4567
|
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: Knopf | Statement: [Penguin Random House, hasImprint, Knopf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knopf Context triple: [Penguin Random House, hasImprint, Knopf]
-
A.
Random House
Random House is a major American book publishing company known for releasing a wide range of influential fiction and nonfiction titles.
-
B.
Henry Holt
Henry Holt was an American publisher and co-founder of the prominent New York publishing house Henry Holt and Company in the late 19th century.
-
C.
Doubleday
Doubleday is a major American publishing company known for releasing a wide range of influential fiction and nonfiction books.
-
D.
Alfred A. Knopf
chosen
Alfred A. Knopf is a prestigious American publishing house known for its high-quality literary fiction and nonfiction titles.
-
E.
Simon & Schuster
Simon & Schuster is a major American publishing company known for producing a wide range of bestselling fiction and nonfiction books.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62d3c57c81908887844e885062e3 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0aaf7a008190bf7e5808838c6c2b |
completed | March 8, 2026, 11:47 p.m. |
Created at: March 4, 2026, 7:30 p.m.