Triple
T16164966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drink with the Devil |
E392279
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | HarperCollins |
E65842
|
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: HarperCollins | Statement: [Drink with the Devil, publisher, HarperCollins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HarperCollins Context triple: [Drink with the Devil, publisher, HarperCollins]
-
A.
HarperCollins
chosen
HarperCollins is a major global publishing company known for producing a wide range of fiction, non-fiction, and educational books.
-
B.
Simon & Schuster
Simon & Schuster is a major American publishing company known for producing a wide range of bestselling fiction and nonfiction books.
-
C.
Penguin Random House
Penguin Random House is a major global trade book publisher known for its extensive catalog of fiction and nonfiction titles across numerous imprints.
-
D.
Macmillan Publishers
Macmillan Publishers is a major global publishing company known for its wide range of academic, educational, and trade books and imprints.
-
E.
Random House
Random House is a major American book publishing company known for releasing a wide range of influential fiction and nonfiction titles.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e622ae481909f3cf25b38886d3a |
completed | April 17, 2026, 11:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000785fcd481909ddf92cf9cc5c0aa |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:02 a.m.