Triple
T11033618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margate Main Sands |
E260819
|
entity |
| Predicate | hasSafetyInformation |
P97409
|
FINISHED |
| Object | bathing water quality monitored in season |
—
|
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: bathing water quality monitored in season | Statement: [Margate Main Sands, hasSafetyInformation, bathing water quality monitored in season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyInformation Context triple: [Margate Main Sands, hasSafetyInformation, bathing water quality monitored in season]
-
A.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
B.
safetyLabel
Indicates that an entity has been assigned a safety-related classification or warning status.
-
C.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
-
D.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
E.
safetyProfile
Indicates the overall level and characteristics of risk or harm associated with something, typically summarizing how safe it is under specified conditions.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797e709648190adbb05197e15ff76 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:25 p.m.