Triple
T27008115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man Who Smiled |
E680302
|
entity |
| Predicate | seriesNumberInKurtWallanderSeries |
P170965
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [The Man Who Smiled, seriesNumberInKurtWallanderSeries, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesNumberInKurtWallanderSeries Context triple: [The Man Who Smiled, seriesNumberInKurtWallanderSeries, 4]
-
A.
reporterSeriesNumber
Indicates the numerical designation of a particular series within a set of reports or reporter publications.
-
B.
seriesNumberInAdventureSeries
Indicates the position or installment number that an item occupies within an adventure series.
-
C.
seriesNumberInCarryOn
Indicates that an item has a specific series or sequence number within a set of carry-on items.
-
D.
filmSeriesInstallmentNumber
Indicates the specific sequential position that a film occupies within a film series.
-
E.
seriesVolumeNumber
Indicates the specific volume number assigned to an item within an ordered series.
- F. None of above. chosen
Provenance (4 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 27, 2026, 7:02 a.m.