Triple
T6148119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Bakr al-Baghdadi |
E137129
|
entity |
| Predicate | bountyAmount |
P30868
|
FINISHED |
| Object | 25000000 USD |
—
|
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: 25000000 USD | Statement: [Abu Bakr al-Baghdadi, bountyAmount, 25000000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bountyAmount Context triple: [Abu Bakr al-Baghdadi, bountyAmount, 25000000 USD]
-
A.
bounty
chosen
Indicates that a reward or payment is offered for performing a specific action or achieving a particular outcome related to an entity.
-
B.
awardAmount
Indicates the specific quantity or value of an award that is granted in the context of a particular awarding event or relationship.
-
C.
authorizedBondAmount
Indicates the maximum bond value that has been formally approved or permitted for issuance or use in a given context.
-
D.
offeredRewardTo
Indicates that one entity has proposed or promised a reward to another entity, typically as an incentive for a specific action or outcome.
-
E.
monetaryValue
Indicates the amount of money associated with an entity, event, or transaction.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05ce07fb081909278088e9e2e2959 |
completed | March 22, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:16 p.m.