Triple
T34502291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | abduction of Europa |
E885789
|
entity |
| Predicate | involvesAbductionOf |
P195248
|
FINISHED |
| Object | Europa |
—
|
NE NERFINISHED |
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: Europa | Statement: [abduction of Europa, involvesAbductionOf, Europa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesAbductionOf Context triple: [abduction of Europa, involvesAbductionOf, Europa]
-
A.
abductionCause
Indicates a causal relationship where one entity is the reason or driving factor behind another entity’s abduction.
-
B.
abductionResultedIn
Indicates that an act of abduction caused or led directly to a particular outcome or consequence.
-
C.
abductionContext
Indicates a contextual relationship in which an abduction event occurs, specifying the surrounding circumstances, conditions, or setting of that abduction.
-
D.
abductionIntendedFor
Indicates that an abduction is carried out with the specific purpose or intended outcome of affecting or involving a particular target or beneficiary.
-
E.
usedAbductions
Indicates that one entity carried out or relied on abductions (kidnappings) as a method or tactic in relation to another entity or context.
- 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
| PDg | Predicate description generation | batch_69fdb3172b808190b590d7c5be31ebb7 |
completed | May 8, 2026, 9:55 a.m. |
Created at: May 1, 2026, 2:01 a.m.