Triple
T10215178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe County Airport (Indiana) |
E242421
|
entity |
| Predicate | IATACode |
P418
|
FINISHED |
| Object |
BMG
BMG is the IATA airport code for Monroe County Airport serving Bloomington, Indiana.
|
E850034
|
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: BMG | Statement: [Monroe County Airport (Indiana), IATACode, BMG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BMG Context triple: [Monroe County Airport (Indiana), IATACode, BMG]
-
A.
BMG
BMG is the commonly used abbreviation for Germany’s Federal Ministry of Health.
-
B.
BMG
BMG is a major global music company known for its music publishing and recorded music services, representing a wide range of international artists and catalogs.
-
C.
BMG Classics
BMG Classics was the classical music division and record label of Bertelsmann Music Group, known for releasing and distributing classical recordings by major orchestras, conductors, and soloists.
-
D.
BMG India
BMG India was the Indian division of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Indian market.
-
E.
BMG Korea
BMG Korea was the South Korean branch of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Korean market.
- 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: BMG Triple: [Monroe County Airport (Indiana), IATACode, BMG]
Generated description
BMG is the IATA airport code for Monroe County Airport serving Bloomington, Indiana.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BMG Target entity description: BMG is the IATA airport code for Monroe County Airport serving Bloomington, Indiana.
-
A.
BMG
BMG is the commonly used abbreviation for Germany’s Federal Ministry of Health.
-
B.
BMG
BMG is a major global music company known for its music publishing and recorded music services, representing a wide range of international artists and catalogs.
-
C.
BMG Classics
BMG Classics was the classical music division and record label of Bertelsmann Music Group, known for releasing and distributing classical recordings by major orchestras, conductors, and soloists.
-
D.
BMG India
BMG India was the Indian division of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Indian market.
-
E.
BMG Korea
BMG Korea was the South Korean branch of the global music company Bertelsmann Music Group, responsible for producing and distributing music in the Korean market.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa273bdc8190bc4cf67a7923cebc |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652f1ffb88190986ea53749fc5e03 |
completed | April 8, 2026, 1:06 p.m. |
| NEDg | Description generation | batch_69d656d55ff481909b84c033aa0f0fc2 |
completed | April 8, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d658a657488190ab08071889af4fb6 |
completed | April 8, 2026, 1:31 p.m. |
Created at: April 6, 2026, 11:04 a.m.