Triple
T36284874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (2019) |
E893048
|
entity |
| Predicate | hasSafetyCompliance |
P17338
|
FINISHED |
| Object | modern passenger-ship regulations |
—
|
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: modern passenger-ship regulations | Statement: [SS Empress of Britain (2019), hasSafetyCompliance, modern passenger-ship regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyCompliance Context triple: [SS Empress of Britain (2019), hasSafetyCompliance, modern passenger-ship regulations]
-
A.
hasSafetyRegulationCompliance
chosen
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
B.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
-
C.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
D.
hasSafetyConfiguration
Indicates that an entity is associated with or assigned a particular safety-related setup, parameters, or protective settings.
-
E.
hasSecurityStandard
Indicates that an entity complies with, follows, or is governed by a specified security standard or framework.
- 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_69f76e4955c08190b8cfddca34fc0242 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.