Triple
T19378663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shipwreck Coast |
E484736
|
entity |
| Predicate | hasHighRiskOf |
P60801
|
FINISHED |
| Object | shipwrecks |
—
|
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: shipwrecks | Statement: [Shipwreck Coast, hasHighRiskOf, shipwrecks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighRiskOf Context triple: [Shipwreck Coast, hasHighRiskOf, shipwrecks]
-
A.
hasHigh
Indicates that an entity possesses a high level, degree, or intensity of a specified attribute or property.
-
B.
hasHazardLevel
chosen
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
C.
hasCountryOfRisk
Indicates that an entity is associated with a country where it faces significant exposure, vulnerability, or potential risk.
-
D.
hasHighChanceOfSurvival
Indicates that the subject is very likely to continue living or remain viable under the given conditions.
-
E.
hasWithdrawalRisk
Indicates that discontinuing or reducing something is associated with a risk of withdrawal effects or adverse reactions.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5dc3048190830b55c8ca02e624 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd54f8e48190956e73dd8969164a |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.