Triple
T13786762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harlequin Enterprises |
E331277
|
entity |
| Predicate | typicalBookLength |
P18065
|
FINISHED |
| Object | short novel |
—
|
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: short novel | Statement: [Harlequin Enterprises, typicalBookLength, short novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBookLength Context triple: [Harlequin Enterprises, typicalBookLength, short novel]
-
A.
typicalLength
chosen
Indicates the usual or characteristic length associated with an entity or phenomenon.
-
B.
propheticBookLength
Indicates the length or extent (such as number of chapters, verses, or words) of a prophetic book.
-
C.
intendedNumberOfBooks
Indicates the number of books that an agent plans or aims to have, produce, read, or otherwise be associated with, as opposed to the number actually realized.
-
D.
numberOfBooks
Indicates the quantity of books associated with a given entity.
-
E.
numberOfChapters
Indicates the total count of chapters associated with 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0249e4f88190a80316394940627d |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbc85fb600819098a2aab48169be96 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:11 p.m.