Triple
T4261069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor-General of Malta |
E96104
|
entity |
| Predicate | country |
P26
|
FINISHED |
| Object | Malta |
E9342
|
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: Malta | Statement: [Governor-General of Malta, country, Malta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malta Context triple: [Governor-General of Malta, country, Malta]
-
A.
Malta
chosen
Malta is a small island nation in the central Mediterranean known for its rich history, strategic location, and membership in the European Union.
-
B.
Malta
Malta is a town in Saratoga County, New York, known for its mix of suburban communities, rural landscapes, and the high-tech Luther Forest Technology Campus.
-
C.
Żebbuġ, Malta
Żebbuġ is a historic town in central Malta known for its traditional architecture, parish church, and long-standing cultural and religious festivities.
-
D.
San Marino
San Marino is a small, landlocked microstate surrounded by Italy, known as one of the world’s oldest republics and a popular tourist destination.
-
E.
San Marino
San Marino is a small, affluent residential city in Los Angeles County, California, known for its high-ranking schools and the Huntington Library, Art Museum, and Botanical Gardens.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f8103b48190934a810faafa6cb7 |
completed | March 12, 2026, 11:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b78c93c48190a4274f0de3fc2d25 |
completed | March 14, 2026, 7:31 p.m. |
Created at: March 12, 2026, 11:06 p.m.