Triple
T23878084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack the Ripper |
E600121
|
entity |
| Predicate | numberOfCanonicalVictims |
P26914
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Jack the Ripper, numberOfCanonicalVictims, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCanonicalVictims Context triple: [Jack the Ripper, numberOfCanonicalVictims, 5]
-
A.
numberOfVictimsTargeted
Indicates the quantity of victims that were intended or selected as targets in the referenced act or event.
-
B.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
C.
hasVictimsCount
Indicates the number of victims associated with a particular event, action, or entity.
-
D.
estimatedVictimsUnderAuthority
Indicates that a specified authority is estimated to have a certain number of victims under its control, influence, or jurisdiction.
-
E.
hasVictimCount
chosen
Indicates the number of victims associated with a particular event, action, or 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cc032c9c81909986ae6f672c1ad1 |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:23 p.m.