Triple
T216090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Restaurant at the End of the Universe |
E4107
|
entity |
| Predicate | hasPageCount |
P1468
|
FINISHED |
| Object | 250 (approximate, varies by edition) |
—
|
LITERAL 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: 250 (approximate, varies by edition) | Statement: [The Restaurant at the End of the Universe, hasPageCount, 250 (approximate, varies by edition)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPageCount Context triple: [The Restaurant at the End of the Universe, hasPageCount, 250 (approximate, varies by edition)]
-
A.
hasTotalNumber
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
-
B.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
C.
pages
chosen
Indicates that one entity consists of or contains a certain number of pages, or that a specific page-related attribute is associated with it.
-
D.
hasPrintVersion
Indicates that one entity exists or is available as a printed or physical edition of another entity.
-
E.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
- F. None of above.
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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.