Triple
T34333952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Region of Malta |
E881093
|
entity |
| Predicate | containsTouristDestination |
P5121
|
FINISHED |
| Object |
Paradise Bay
Paradise Bay is a small, picturesque sandy beach and popular swimming spot in northern Malta, known for its clear turquoise waters and scenic cliffs.
|
E2090719
|
NE 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: Paradise Bay | Statement: [Northern Region of Malta, containsTouristDestination, Paradise Bay]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Paradise Bay Triple: [Northern Region of Malta, containsTouristDestination, Paradise Bay]
Generated description
Paradise Bay is a small, picturesque sandy beach and popular swimming spot in northern Malta, known for its clear turquoise waters and scenic cliffs.
Provenance (5 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_69f349ba96a08190b94887bae2d8ee49 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f713c0ba4881909d6e200215ad13eb |
completed | May 3, 2026, 9:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36f9dbc3348190a62e9737d592d847 |
completed | June 20, 2026, 8:36 p.m. |
| NEDg | Description generation | batch_6a36fa9d7f4881908aabcf2a4c5a8230 |
completed | June 20, 2026, 8:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a36fb4d8d6881909a9ffcf6817db26f |
completed | June 20, 2026, 8:42 p.m. |
Created at: May 1, 2026, 1:58 a.m.