Triple
T15807444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grant County International Airport |
E383254
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
KMWH
KMWH is the ICAO airport code for Grant County International Airport, a large public airport in Moses Lake, Washington, known for its long runways and use as a military and aircraft testing facility.
|
E1177801
|
NE FINISHED |
How this triple was built (4 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: KMWH | Statement: [Grant County International Airport, ICAOcode, KMWH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KMWH Context triple: [Grant County International Airport, ICAOcode, KMWH]
-
A.
KMH
KMH is the Royal College of Music in Stockholm, a leading Swedish institution for higher education in music performance, composition, and pedagogy.
-
B.
KMW
KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
-
C.
KM
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
D.
KM
KM is the abbreviation for Kabataang Makabayan, a historic left-wing nationalist youth organization in the Philippines.
-
E.
KMHR
KMHR is the ICAO airport code for Mather Airport, a public airport located near Sacramento, California.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: KMWH Triple: [Grant County International Airport, ICAOcode, KMWH]
Generated description
KMWH is the ICAO airport code for Grant County International Airport, a large public airport in Moses Lake, Washington, known for its long runways and use as a military and aircraft testing facility.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KMWH Target entity description: KMWH is the ICAO airport code for Grant County International Airport, a large public airport in Moses Lake, Washington, known for its long runways and use as a military and aircraft testing facility.
-
A.
KMH
KMH is the Royal College of Music in Stockholm, a leading Swedish institution for higher education in music performance, composition, and pedagogy.
-
B.
KMW
KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
-
C.
KM
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
D.
KM
KM is the abbreviation for Kabataang Makabayan, a historic left-wing nationalist youth organization in the Philippines.
-
E.
KMHR
KMHR is the ICAO airport code for Mather Airport, a public airport located near Sacramento, California.
- F. None of above. chosen
Provenance (5 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52751348190964e82463ce9dd20 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff998fa5588190b28efc2f342405aa |
completed | May 9, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69ff9a32d6bc81909d8023de562a2517 |
completed | May 9, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff9adb25448190b805046ae6c3ee17 |
completed | May 9, 2026, 8:36 p.m. |
Created at: April 10, 2026, 4:48 a.m.