Triple
T12399979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juanda International Airport |
E296225
|
entity |
| Predicate | icaoCode |
P419
|
FINISHED |
| Object | WARR |
E296225
|
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: WARR | Statement: [Juanda International Airport, icaoCode, WARR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WARR Context triple: [Juanda International Airport, icaoCode, WARR]
-
A.
WARR
chosen
WARR is the ICAO airport code for Juanda International Airport, a major airport serving Surabaya in East Java, Indonesia.
-
B.
WARJ
WARJ is the ICAO airport code for Adisutjipto International Airport serving the Yogyakarta area in Indonesia.
-
C.
WRAN
WRAN (Wireless Regional Area Network) is a broadband wireless networking standard designed to provide high-speed internet access over large rural and remote areas using unused TV broadcast spectrum.
-
D.
WARA
WARA is the ICAO airport code for Abdul Rachman Saleh Airport in Malang, East Java, Indonesia.
-
E.
AWRP
AWRP is a collaborative initiative focused on restoring and protecting the environmental health and water quality of the Anacostia River watershed.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9401cbfd481908ee6e765da3d12cb |
completed | April 10, 2026, 6:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63482af8c8190b277b36371979f5e |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.