Triple
T37826288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flesh and Blood |
E943067
|
entity |
| Predicate | workSeriesNumberApproximate |
P61667
|
FINISHED |
| Object | 22nd Kay Scarpetta 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: 22nd Kay Scarpetta novel | Statement: [Flesh and Blood, workSeriesNumberApproximate, 22nd Kay Scarpetta novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workSeriesNumberApproximate Context triple: [Flesh and Blood, workSeriesNumberApproximate, 22nd Kay Scarpetta novel]
-
A.
seriesNumberOfWorks
Indicates that an entity is assigned a specific position or sequence number within a series of related works.
-
B.
hasSeriesNumber
chosen
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
C.
workCountInSeries
Indicates the number of individual works that belong to a particular series.
-
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.
numberOfSeries
Indicates the total count of distinct series associated with or contained within 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: May 3, 2026, 4:19 p.m.