Triple
T8669619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simon Ross |
E205761
|
entity |
| Predicate | reasonForTargeting |
P69059
|
FINISHED |
| Object | investigation into Jason Bourne |
—
|
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: investigation into Jason Bourne | Statement: [Simon Ross, reasonForTargeting, investigation into Jason Bourne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForTargeting Context triple: [Simon Ross, reasonForTargeting, investigation into Jason Bourne]
-
A.
targetedBecauseOf
chosen
Indicates that one entity is made a target of an action, harm, or scrutiny specifically due to possessing a particular attribute, identity, or characteristic.
-
B.
selectionReason
Indicates the reason or justification for choosing or selecting one entity over alternatives.
-
C.
statedReason
Indicates that one entity expresses or provides another entity as the explanation, justification, or motive for an action, event, or claim.
-
D.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
E.
incomeTargetingRequirement
Indicates that a condition or rule specifies required income levels or ranges that must be met for eligibility or targeting purposes.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4917cb9881909a73b74e54250613 |
completed | March 31, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:31 p.m.