Triple
T3565371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe Regional Airport |
E75434
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
KMLU
KMLU is the ICAO airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
|
E369377
|
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: KMLU | Statement: [Monroe Regional Airport, ICAOcode, KMLU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KMLU Context triple: [Monroe Regional Airport, ICAOcode, KMLU]
-
A.
KTLH
KTLH is the ICAO airport code for Tallahassee International Airport, the primary commercial airport serving Florida’s capital city.
-
B.
KTVL
KTVL is the ICAO airport code for Lake Tahoe Airport, a public airport serving the Lake Tahoe region in California.
-
C.
KLGB
KLGB is the ICAO airport code for Long Beach Airport, a public airport in Long Beach, California, serving commercial, general aviation, and cargo flights in the Los Angeles area.
-
D.
KSMF
KSMF is the ICAO airport code for Sacramento International Airport, a major commercial airport serving California’s capital region.
-
E.
KCLT
KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
- 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: KMLU Triple: [Monroe Regional Airport, ICAOcode, KMLU]
Generated description
KMLU is the ICAO airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KMLU Target entity description: KMLU is the ICAO airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
-
A.
KTLH
KTLH is the ICAO airport code for Tallahassee International Airport, the primary commercial airport serving Florida’s capital city.
-
B.
KTVL
KTVL is the ICAO airport code for Lake Tahoe Airport, a public airport serving the Lake Tahoe region in California.
-
C.
KLGB
KLGB is the ICAO airport code for Long Beach Airport, a public airport in Long Beach, California, serving commercial, general aviation, and cargo flights in the Los Angeles area.
-
D.
KSMF
KSMF is the ICAO airport code for Sacramento International Airport, a major commercial airport serving California’s capital region.
-
E.
KCLT
KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
- 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0a8f6288190928479f5bea32245 |
completed | March 8, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bbacbb1081908fc57168a8fc3ade |
completed | March 13, 2026, 7:24 a.m. |
| NEDg | Description generation | batch_69b3bf78d6a881908d5bcc4ae50a76e5 |
completed | March 13, 2026, 7:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3f5adac0481908b9053585c317be0 |
completed | March 13, 2026, 11:31 a.m. |
Created at: March 8, 2026, 3:21 p.m.