Triple
T2745571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Shipman |
E60857
|
entity |
| Predicate | ShipmanInquiryFinding |
P25771
|
FINISHED |
| Object | likely killed over 200 patients |
—
|
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: likely killed over 200 patients | Statement: [Harold Shipman, ShipmanInquiryFinding, likely killed over 200 patients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ShipmanInquiryFinding Context triple: [Harold Shipman, ShipmanInquiryFinding, likely killed over 200 patients]
-
A.
shipCompanion
Indicates that one entity serves as a companion or partner accompanying another entity on a ship or sea voyage.
-
B.
finds
Indicates that one entity discovers, locates, or comes upon another entity, often as the result of a search or encounter.
-
C.
containsFinding
chosen
Indicates that one entity includes, encompasses, or holds a particular finding as part of its content or results.
-
D.
hasShip
Indicates that one entity possesses, owns, or is equipped with a ship.
-
E.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
- 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb4d37a481908cc2ad4666f3ac94 |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd829f1e88190aab1d54f87c69714 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.