Triple
T6612313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modesto City–County Airport |
E149264
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
KMOD
KMOD is the ICAO airport code for Modesto City–County Airport in Modesto, California.
|
E601005
|
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: KMOD | Statement: [Modesto City–County Airport, ICAOcode, KMOD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KMOD Context triple: [Modesto City–County Airport, ICAOcode, KMOD]
-
A.
Modulen
Modulen is a specialized medical nutrition product line from Nestlé Health Science, commonly used in the dietary management of conditions such as Crohn’s disease.
-
B.
MOD
MOD is the commonly used abbreviation for Japan’s Ministry of Defense, the government body responsible for the country’s national defense and Self-Defense Forces.
-
C.
MOD
MOD is the commonly used abbreviation for the United Kingdom’s Ministry of Defence, the government department responsible for implementing defense policy and overseeing the armed forces.
-
D.
DKMS
DKMS is the abbreviated name of the Dimitrov Communist Youth Union, a communist youth organization historically active in Bulgaria.
-
E.
MODS
MODS (Metadata Object Description Schema) is a bibliographic metadata standard developed by the Library of Congress that provides a rich, XML-based format for describing digital and print resources.
- 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: KMOD Triple: [Modesto City–County Airport, ICAOcode, KMOD]
Generated description
KMOD is the ICAO airport code for Modesto City–County Airport in Modesto, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KMOD Target entity description: KMOD is the ICAO airport code for Modesto City–County Airport in Modesto, California.
-
A.
Modulen
Modulen is a specialized medical nutrition product line from Nestlé Health Science, commonly used in the dietary management of conditions such as Crohn’s disease.
-
B.
MOD
MOD is the commonly used abbreviation for Japan’s Ministry of Defense, the government body responsible for the country’s national defense and Self-Defense Forces.
-
C.
MOD
MOD is the commonly used abbreviation for the United Kingdom’s Ministry of Defence, the government department responsible for implementing defense policy and overseeing the armed forces.
-
D.
DKMS
DKMS is the abbreviated name of the Dimitrov Communist Youth Union, a communist youth organization historically active in Bulgaria.
-
E.
MODS
MODS (Metadata Object Description Schema) is a bibliographic metadata standard developed by the Library of Congress that provides a rich, XML-based format for describing digital and print resources.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af3778a8819094e83afed7c6596f |
completed | March 27, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cbd651c08190a19513645fc781c9 |
completed | March 27, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69c6cd89b51c81909ea17d391732630e |
completed | March 27, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6ce70442c8190a12a6c6eb76c5269 |
completed | March 27, 2026, 6:37 p.m. |
Created at: March 27, 2026, 1:57 p.m.