Triple
T31734552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Black Book |
E809956
|
entity |
| Predicate | seriesNumberInInspectorRebus |
P61667
|
FINISHED |
| Object | fifth 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: fifth novel | Statement: [The Black Book, seriesNumberInInspectorRebus, fifth novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesNumberInInspectorRebus Context triple: [The Black Book, seriesNumberInInspectorRebus, fifth novel]
-
A.
reporterSeriesNumber
Indicates the numerical designation of a particular series within a set of reports or reporter publications.
-
B.
seriesNumberInCarryOn
Indicates that an item has a specific series or sequence number within a set of carry-on items.
-
C.
hasSeriesNumber
chosen
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
D.
seriesOf
Indicates that one entity is a sequence or ordered set of related items, events, or parts that collectively form or belong to another entity.
-
E.
designationSeries
Indicates that one designation belongs to or is part of a broader series of related designations.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 30, 2026, 11:22 p.m.