Triple
T14098366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Jorge Airport |
E339313
|
entity |
| Predicate | pushpinLabel |
P9248
|
FINISHED |
| Object | SJZ |
E1079936
|
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: SJZ | Statement: [São Jorge Airport, pushpinLabel, SJZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SJZ Context triple: [São Jorge Airport, pushpinLabel, SJZ]
-
A.
SJZ
chosen
SJZ is the IATA airport code for São Jorge Airport, which serves the island of São Jorge in Portugal’s Azores archipelago.
-
B.
ZSJN
ZSJN is the ICAO airport code for Jinan Yaoqiang International Airport, the main commercial airport serving Jinan in Shandong Province, China.
-
C.
ZSXZ
ZSXZ is the ICAO airport code assigned to Xuzhou Guanyin International Airport in Xuzhou, Jiangsu Province, China.
-
D.
SJ
SJ is Sweden’s primary state-owned passenger train operator, running long-distance and regional rail services across the country.
-
E.
SJ
SJ is the vehicle registration code used on license plates for cars registered in Jaworzno, Poland.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb926288190a7f0f50d1d585d76 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf02638881908eff75453b6a2aab |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:22 p.m.