Triple
T11835385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newcastle International Airport |
E281502
|
entity |
| Predicate | hasIATAcode |
P2569
|
FINISHED |
| Object | NCL |
E281502
|
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: NCL | Statement: [Newcastle International Airport, hasIATAcode, NCL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NCL Context triple: [Newcastle International Airport, hasIATAcode, NCL]
-
A.
NCL
NCL is the commonly used abbreviation for the Nice Classification, an international system for categorizing goods and services for trademark registration.
-
B.
NCL
NCL is the three-letter National Rail station code for Newcastle railway station, a major rail hub in Newcastle upon Tyne, England.
-
C.
NCL
chosen
NCL is the IATA airport code for Newcastle International Airport, a major airport serving Newcastle upon Tyne and the surrounding region in northeast England.
-
D.
NetCDF
NetCDF is a widely used, self-describing, machine-independent data format and set of software libraries designed for storing and sharing array-oriented scientific data, especially in the geosciences.
-
E.
NCDC
NCDC is Uganda’s National Curriculum Development Centre, the government body responsible for designing and reviewing the country’s education curricula and related materials.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62e7e408190998bebe346c82e89 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f16765aac481908b4cb474b141d842 |
completed | April 29, 2026, 2:05 a.m. |
Created at: April 8, 2026, 9:43 p.m.