Triple
T7143703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Mayaguez |
E166511
|
entity |
| Predicate | incidentCharacterization |
P75088
|
FINISHED |
| Object | act of piracy as claimed by the United States |
—
|
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: act of piracy as claimed by the United States | Statement: [SS Mayaguez, incidentCharacterization, act of piracy as claimed by the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incidentCharacterization Context triple: [SS Mayaguez, incidentCharacterization, act of piracy as claimed by the United States]
-
A.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
B.
medicalEvent
Indicates that a specific health-related occurrence or clinical incident has taken place involving one or more entities.
-
C.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
E.
investigatedEvent
Indicates that an event was the subject of an investigation or inquiry carried out by some agent.
- 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_69c6888579d481909e05a8d6b81bf733 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7d027d0819088598b2a9f71b1b7 |
completed | March 27, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c932888190b125ca3785b18553 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:46 p.m.