Triple
T31138507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carrickarede |
E793713
|
entity |
| Predicate | hasLandfallOf |
P196090
|
FINISHED |
| Object | Carrick-a-Rede Rope Bridge |
—
|
NE NERFINISHED |
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: Carrick-a-Rede Rope Bridge | Statement: [Carrickarede, hasLandfallOf, Carrick-a-Rede Rope Bridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandfallOf Context triple: [Carrickarede, hasLandfallOf, Carrick-a-Rede Rope Bridge]
-
A.
firstLandfallBy
Indicates the location or entity where something (typically a storm, traveler, or object) initially makes landfall or first arrives from a journey over water or air.
-
B.
didNotMakeLandfall
Indicates that a storm or weather system remained over water and never crossed onto land.
-
C.
dateOfLandfall
Indicates the specific calendar date on which a storm or similar event first makes landfall at a particular location.
-
D.
stormTypeAtLandfall
Indicates the classification or category of a storm at the specific time and location where it makes landfall.
-
E.
hasTropicalCyclones
Indicates that the specified region or area experiences tropical cyclones as part of its typical weather or climate 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
| PDg | Predicate description generation | batch_69fe066b623c819085205fbea901e3cf |
completed | May 8, 2026, 3:51 p.m. |
Created at: April 29, 2026, 9:05 p.m.