Triple
T32813961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hijacking of the Achille Lauro |
E839232
|
entity |
| Predicate | portraysVictim |
P6323
|
FINISHED |
| Object | disabled American passenger |
—
|
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: disabled American passenger | Statement: [The Hijacking of the Achille Lauro, portraysVictim, disabled American passenger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysVictim Context triple: [The Hijacking of the Achille Lauro, portraysVictim, disabled American passenger]
-
A.
portraysAsVictim
chosen
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
B.
allegedVictimOf
Indicates that one entity is claimed or reported to have been harmed, wronged, or victimized by another entity, without asserting that the claim is proven.
-
C.
isVictimOf
Indicates that one entity suffers harm, loss, or wrongdoing as a result of another entity’s actions or events.
-
D.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
-
E.
honorsVictimOf
Indicates that one entity pays tribute or respect to another entity who has suffered harm, loss, or injustice.
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe920a437081908d5174e8cf7a53a6 |
completed | May 9, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69fe919a9a6c8190acb4483f386e6db7 |
completed | May 9, 2026, 1:44 a.m. |
Created at: May 1, 2026, 1:15 a.m.