Triple
T12092736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terre Haute Regional Airport |
E287987
|
entity |
| Predicate | FAAcode |
P420
|
FINISHED |
| Object | HUF |
E634593
|
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: HUF | Statement: [Terre Haute Regional Airport, FAAcode, HUF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HUF Context triple: [Terre Haute Regional Airport, FAAcode, HUF]
-
A.
HUF
chosen
HUF is the currency code for the Hungarian forint, the official currency of Hungary.
-
B.
HUCH
HUCH is a major Finnish hospital complex that serves as the central teaching and research hospital for the University of Helsinki and a key provider of specialized medical care in the Helsinki region.
-
C.
Ugg
Ugg is a popular footwear and lifestyle brand best known for its sheepskin boots and casual comfort-focused products.
-
D.
Bata
Bata is a major port city on the mainland of Equatorial Guinea, serving as a key economic and transportation hub for the country.
-
E.
Hilfiger Denim
Hilfiger Denim is a casual clothing line under the Tommy Hilfiger fashion label, focusing on youthful, denim-centered apparel with a classic American style.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9151797988190b0d007ea806bcf02 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a6f22cc8190ba12c910c5ef5868 |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:48 p.m.