Triple
T24070432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | murder of Albert Snyder |
E596209
|
entity |
| Predicate | hasInsurancePolicyOnVictim |
P154747
|
FINISHED |
| Object | life insurance policy on Albert Snyder |
—
|
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: life insurance policy on Albert Snyder | Statement: [murder of Albert Snyder, hasInsurancePolicyOnVictim, life insurance policy on Albert Snyder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInsurancePolicyOnVictim Context triple: [murder of Albert Snyder, hasInsurancePolicyOnVictim, life insurance policy on Albert Snyder]
-
A.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
-
B.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
C.
hasModeOfTransportInAccident
Indicates that a specific mode of transport was involved in an accident associated with the given entity.
-
D.
hasIndemnity
Indicates that one party provides indemnification or protection to another party against specified losses, damages, or liabilities.
-
E.
isOnPolicy
Indicates that an action, configuration, or behavior complies with and adheres to a specified policy or set of rules.
- F. None of above. chosen
Provenance (4 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db17c99881909f97e858fb183d86 |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:41 p.m.