Triple
T15732291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murmansk Airport |
E381373
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
ULMM
ULMM is the ICAO airport code assigned to Murmansk Airport in Russia.
|
E1174517
|
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: ULMM | Statement: [Murmansk Airport, ICAOcode, ULMM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ULMM Context triple: [Murmansk Airport, ICAOcode, ULMM]
-
A.
UMM
UMM is a private Islamic university in Malang, Indonesia, affiliated with the Muhammadiyah organization and known for its wide range of academic programs.
-
B.
UMM
UMM is a small public liberal arts college campus of the University of Minnesota system located in Morris, Minnesota.
-
C.
UL
UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
-
D.
UL
UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
-
E.
UL
UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
- 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: ULMM Triple: [Murmansk Airport, ICAOcode, ULMM]
Generated description
ULMM is the ICAO airport code assigned to Murmansk Airport in Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ULMM Target entity description: ULMM is the ICAO airport code assigned to Murmansk Airport in Russia.
-
A.
UMM
UMM is a private Islamic university in Malang, Indonesia, affiliated with the Muhammadiyah organization and known for its wide range of academic programs.
-
B.
UMM
UMM is a small public liberal arts college campus of the University of Minnesota system located in Morris, Minnesota.
-
C.
UL
UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
-
D.
UL
UL is the vehicle registration code for the district that includes the municipality of Lauterach in Austria.
-
E.
UL
UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd3614481908b2694b1d3550058 |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82fed7888190b45f28ac91e0079e |
completed | May 9, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_69ff83b7a534819090e24491579376c3 |
completed | May 9, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff844fa00c8190a47eb46394db097b |
completed | May 9, 2026, 7 p.m. |
Created at: April 10, 2026, 4:46 a.m.