Triple
T2158431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotus case |
E47945
|
entity |
| Predicate | originatingIncidentType |
P1788
|
FINISHED |
| Object | collision between ships on the high seas |
—
|
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: collision between ships on the high seas | Statement: [Lotus case, originatingIncidentType, collision between ships on the high seas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originatingIncidentType Context triple: [Lotus case, originatingIncidentType, collision between ships on the high seas]
-
A.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
investigatedEvent
Indicates that an event was the subject of an investigation or inquiry carried out by some agent.
-
C.
accidentType
chosen
Indicates the specific category or kind of accident associated with an event or incident.
-
D.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
E.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe68fe0c8190beb5db003738a6e5 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.