Triple
T17955162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Youth (novel by Leo Tolstoy) |
E448926
|
entity |
| Predicate | hasTrilogyPartNumber |
P64761
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Youth (novel by Leo Tolstoy), hasTrilogyPartNumber, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrilogyPartNumber Context triple: [Youth (novel by Leo Tolstoy), hasTrilogyPartNumber, 3]
-
A.
hasPartInTrilogy
Indicates that an entity is one of the constituent parts (e.g., books, films, or episodes) that together form a specific trilogy.
-
B.
partOfTrilogy
Indicates that one work belongs to a set of three related works that together form a trilogy.
-
C.
hasSequelInTrilogy
Indicates that one work in a trilogy is followed by another work that serves as its sequel within that same three-part series.
-
D.
isThirdInSeries
chosen
Indicates that an entity occupies the third position within an ordered sequence or series of related items.
-
E.
hasPartNumber
Indicates that one entity is assigned or associated with a specific part number used to identify it within a catalog, system, or inventory.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afaf1ddc8190b480147ac35a4912 |
completed | April 19, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.