Triple
T5516876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KPUB |
E144705
|
entity |
| Predicate | icaoCode |
P419
|
FINISHED |
| Object | KPUB |
E144705
|
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: KPUB | Statement: [KPUB, icaoCode, KPUB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KPUB Context triple: [KPUB, icaoCode, KPUB]
-
A.
KPUB
chosen
KPUB is the ICAO airport code for Pueblo Memorial Airport, a public airport serving Pueblo, Colorado, in the United States.
-
B.
EPUB
EPUB is a widely used open e-book file format designed for reflowable digital publications that can adapt to different screen sizes and devices.
-
C.
KOMA
KOMA is the ICAO airport code for Eppley Airfield, the primary commercial airport serving Omaha, Nebraska.
-
D.
Pan Books
Pan Books is a British publishing imprint known for producing popular fiction and classic titles, including major science fiction works.
-
E.
Kobo e-readers
Kobo e-readers are a line of digital reading devices known for their wide format support, integration with public libraries, and openness compared to many competing platforms.
- 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f5e8ce08190b7f5f2131bebcd4f |
completed | March 22, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c027dd848481908052007e89c3f634 |
completed | March 22, 2026, 5:33 p.m. |
Created at: March 22, 2026, 3:33 p.m.