Triple
T8329009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pakistan International Airlines |
E195028
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | PK |
E5694
|
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: PK | Statement: [Pakistan International Airlines, IATAcode, PK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PK Context triple: [Pakistan International Airlines, IATAcode, PK]
-
A.
PK
PK is a compact bitmap font file format traditionally used by TeX systems to store rasterized glyphs generated from METAFONT sources.
-
B.
PK
PK is a music producer best known for his work on DMX's influential debut album "It's Dark and Hell Is Hot."
-
C.
PK
chosen
PK is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Pakistan in international standards and systems.
-
D.
KP
KP is the post-nominal abbreviation used by knights of the Order of Saint Patrick, a British order of chivalry associated with Ireland.
-
E.
KP
KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
- 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fb812508190aed8a283dacf712e |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95c2c36481909793e9cd0c28168a |
completed | April 1, 2026, 10:01 p.m. |
Created at: March 30, 2026, 5:56 p.m.