Triple
T28229335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 20th Victim |
E711680
|
entity |
| Predicate | seriesNumberInWomen'sMurderClub |
P175232
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [20th Victim, seriesNumberInWomen'sMurderClub, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesNumberInWomen'sMurderClub Context triple: [20th Victim, seriesNumberInWomen'sMurderClub, 20]
-
A.
seriesNumberInWomen’sMurderClub
chosen
Indicates the position or installment number that a work occupies within the Women’s Murder Club series.
-
B.
mysterySet
Indicates that an entity belongs to a collection or group whose nature, contents, or defining criteria are unknown or intentionally unspecified.
-
C.
mysteryAssociatedWith
Indicates a relationship where something is connected to, involved in, or characterized by an element of mystery or the unknown.
-
D.
murderedIn
Indicates that one entity unlawfully killed another entity at or within a specified location.
-
E.
numberOfMysteries
Indicates the quantity or count of mysteries 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 27, 2026, 10:51 p.m.