Triple
T1329263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SP |
E28602
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Polish airlines |
E50294
|
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: Polish airlines | Statement: [SP, usedBy, Polish airlines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Polish airlines Context triple: [SP, usedBy, Polish airlines]
-
A.
LOT Polish Airlines
chosen
LOT Polish Airlines is the flag carrier of Poland, operating an extensive network of domestic and international flights across Europe, Asia, and North America.
-
B.
Czech Airlines
Czech Airlines is the national flag carrier of the Czech Republic, operating scheduled passenger flights across Europe and to select long-haul destinations.
-
C.
TAROM
TAROM is the national flag carrier airline of Romania, operating domestic and international flights primarily from its hub in Bucharest.
-
D.
Croatia Airlines
Croatia Airlines is the national flag carrier of Croatia, operating domestic and international passenger flights across Europe.
-
E.
Austrian Airlines
Austrian Airlines is the flag carrier airline of Austria, operating an extensive network of European and long-haul flights from its main hub in Vienna.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c30c948190afc6342b3dcda948 |
completed | March 1, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf32b488819095dc63d338a30b9b |
completed | March 8, 2026, 12:13 a.m. |
Created at: March 1, 2026, 7:55 p.m.