Triple
T3052282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyclone Tracy |
E60397
|
entity |
| Predicate | madeLandfallOn |
P45370
|
FINISHED |
| Object | 1974-12-24 |
—
|
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: 1974-12-24 | Statement: [Cyclone Tracy, madeLandfallOn, 1974-12-24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: madeLandfallOn Context triple: [Cyclone Tracy, madeLandfallOn, 1974-12-24]
-
A.
landedNear
Indicates that one entity has come to rest on a surface or location in close proximity to another specified entity or reference point.
-
B.
landedOnBy
Indicates that one entity has come down to rest upon or make contact with the surface of another entity.
-
C.
beachedAt
Indicates that something has come ashore and is stranded or resting on a beach at a particular location or time.
-
D.
landSightedBy
Indicates that a particular area of land has been visually observed or detected by a specified observer.
-
E.
shipwreckedOn
Indicates that an entity becomes stranded or marooned on a particular landmass or location as a result of a shipwreck.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf274f88190a759f9ce3da47c35 |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad9b272a408190ba0ce09bdeea76c9 |
completed | March 8, 2026, 3:52 p.m. |
Created at: March 8, 2026, 3:01 p.m.