Triple
T13759522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manassas Regional Airport |
E330565
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object | HEF |
E330566
|
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: HEF | Statement: [Manassas Regional Airport, IATA code, HEF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HEF Context triple: [Manassas Regional Airport, IATA code, HEF]
-
A.
HEF
chosen
HEF is the FAA location identifier for Manassas Regional Airport in Virginia, a public airport serving general aviation and regional air traffic.
-
B.
HEF
HEF is the German vehicle registration code assigned to the district of Hersfeld-Rotenburg, centered around the town of Bad Hersfeld in Hesse.
-
C.
HAF
HAF is the commonly used abbreviation for the Hellenic Air Force, the air warfare branch of Greece’s armed forces.
-
D.
HE
HE is the Faculty of Health at Aarhus University, responsible for education and research in medical and health sciences.
-
E.
HEE
HEE is the acronym for Health Education England, the national body responsible for overseeing education, training, and workforce development for healthcare staff in England.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0223ab9081909db05334860405e0 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a85dfa6881908da90886db4aa1bb |
completed | May 3, 2026, 7:56 p.m. |
Created at: April 9, 2026, 10:09 p.m.