Triple
T15421044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe Regional Airport |
E369376
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object | MLU |
E369376
|
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: MLU | Statement: [Monroe Regional Airport, IATA code, MLU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLU Context triple: [Monroe Regional Airport, IATA code, MLU]
-
A.
MLU
chosen
MLU is the IATA airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
-
B.
MLN
MLN is the IATA airport code for Melilla Airport, which serves the Spanish autonomous city of Melilla on the north coast of Africa.
-
C.
MMLP
MMLP is the ICAO airport code for Manuel Márquez de León International Airport serving La Paz, Baja California Sur, Mexico.
-
D.
ML-1
ML-1 is Pakistan Railways’ primary north–south main line, connecting major cities and serving as the backbone of the country’s rail transport system.
-
E.
/mlp/
/mlp/ is 4chan’s board dedicated to discussion, content, and fandom surrounding the animated series "My Little Pony."
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ebe7b1081908e6b9e6e128a8d5d |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7adb848190836fb972bc8744f1 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:20 a.m.