Triple
T8201428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Children’s Machine |
E191582
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object | Basic Books |
E32461
|
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: Basic Books | Statement: [The Children’s Machine, publisher, Basic Books]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basic Books Context triple: [The Children’s Machine, publisher, Basic Books]
-
A.
Basic Books
chosen
Basic Books is an American publishing company known for releasing influential works in the fields of social sciences, humanities, and public affairs.
-
B.
Beginner Books
Beginner Books is a popular line of early-reader children's books, originally developed by Dr. Seuss and others to help young children learn to read through simple vocabulary and engaging stories.
-
C.
Basic
Basic is a discount cigarette brand produced and marketed by Philip Morris USA.
-
D.
Basic
Basic is a 2003 mystery-thriller film directed by John McTiernan, centered on a complex investigation into the disappearance of U.S. Army Rangers during a training mission in Panama.
-
E.
Home Basic
Home Basic is an entry-level edition of the Windows Vista operating system designed for basic home computing needs with limited multimedia and advanced features.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df6e7548190846a1afd62ec6d0a |
completed | March 31, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd34a9c8f08190a8a79b7baa7ffded |
completed | April 1, 2026, 3:07 p.m. |
Created at: March 30, 2026, 5:43 p.m.