Triple
T16886798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Darwin |
E421559
|
entity |
| Predicate | amountInvolvedApprox |
P124858
|
FINISHED |
| Object | £25000 life insurance payout |
—
|
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: £25000 life insurance payout | Statement: [John Darwin, amountInvolvedApprox, £25000 life insurance payout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amountInvolvedApprox Context triple: [John Darwin, amountInvolvedApprox, £25000 life insurance payout]
-
A.
approximateValueStolenInUSDAtTheTime
Indicates the estimated amount of money, in U.S. dollars and valued at the time of the theft, that was stolen in the described incident.
-
B.
legalActionSettlementAmount
Indicates the monetary amount agreed upon or ordered to resolve a legal action or dispute.
-
C.
approximateNumberAwarded
Indicates the estimated quantity of awards or recognitions given in a particular context or event.
-
D.
amountDependsOn
Indicates that the quantity or magnitude of one entity is determined by, or varies as a function of, another entity.
-
E.
civilJudgmentAmount
Indicates the monetary value ordered or determined in a civil court judgment between parties.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc1f42481909dcf595358c23497 |
completed | April 18, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e32e2c07b081908c8fee9f5507bb9e |
completed | April 18, 2026, 7:09 a.m. |
Created at: April 10, 2026, 5:29 a.m.