Triple
T4354334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mobile Regional Airport |
E98108
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
KMOB
KMOB is the ICAO airport code for Mobile Regional Airport in Mobile, Alabama, United States.
|
E433094
|
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: KMOB | Statement: [Mobile Regional Airport, ICAOcode, KMOB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KMOB Context triple: [Mobile Regional Airport, ICAOcode, KMOB]
-
A.
KMCO
KMCO is the ICAO airport code for Orlando International Airport, a major commercial airport serving the Orlando, Florida metropolitan area.
-
B.
KSMF
KSMF is the ICAO airport code for Sacramento International Airport, a major commercial airport serving California’s capital region.
-
C.
KMA
KMA is the commonly used abbreviation for the Royal Swedish Academy of Music, Sweden’s national institution dedicated to the advancement of musical art and scholarship.
-
D.
KM
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
E.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
- 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: KMOB Triple: [Mobile Regional Airport, ICAOcode, KMOB]
Generated description
KMOB is the ICAO airport code for Mobile Regional Airport in Mobile, Alabama, United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KMOB Target entity description: KMOB is the ICAO airport code for Mobile Regional Airport in Mobile, Alabama, United States.
-
A.
KMCO
KMCO is the ICAO airport code for Orlando International Airport, a major commercial airport serving the Orlando, Florida metropolitan area.
-
B.
KSMF
KSMF is the ICAO airport code for Sacramento International Airport, a major commercial airport serving California’s capital region.
-
C.
KMA
KMA is the commonly used abbreviation for the Royal Swedish Academy of Music, Sweden’s national institution dedicated to the advancement of musical art and scholarship.
-
D.
KM
KM is the stock ticker symbol formerly used to represent Kmart Corporation, a major American discount department store chain.
-
E.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c3aa1c8190aacebb8e80e5f2f8 |
completed | March 12, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dbb662008190854da50df1147a7c |
completed | March 14, 2026, 10:05 p.m. |
| NEDg | Description generation | batch_69b5dc6a97208190b91d784285657bff |
completed | March 14, 2026, 10:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5dce749708190b9daf2c192b32de3 |
completed | March 14, 2026, 10:10 p.m. |
Created at: March 12, 2026, 11:15 p.m.