Triple
T4484013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 Mediterranean Games |
E107191
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Oran 2022 |
E19574
|
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: Oran 2022 | Statement: [2022 Mediterranean Games, shortName, Oran 2022]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oran 2022 Context triple: [2022 Mediterranean Games, shortName, Oran 2022]
-
A.
Oran
chosen
Oran is a major port city on Algeria’s Mediterranean coast, known for its historical significance, vibrant culture, and role as an important economic center.
-
B.
Orly 2
Orly 2 is one of the main passenger terminals at Paris Orly Airport, serving as a hub for various domestic and international flights.
-
C.
Ors
Ors is a small commune in northern France, known for its World War I history and military cemetery.
-
D.
ORC
ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
-
E.
ORC
ORC is the abbreviation for the Organized Reserve Corps, a former component of the United States Army Reserve structure.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd52a54c6c8190a7421bea6e3c00f1 |
completed | March 20, 2026, 1:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd679792f48190a19ce4ab91cab3bc |
completed | March 20, 2026, 3:28 p.m. |
Created at: March 20, 2026, 12:58 p.m.