Triple
T6612312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modesto City–County Airport |
E149264
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object | MOD |
E109651
|
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: MOD | Statement: [Modesto City–County Airport, IATAcode, MOD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MOD Context triple: [Modesto City–County Airport, IATAcode, MOD]
-
A.
MOD
chosen
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.
-
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.
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.
-
D.
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.
-
E.
MUT
MUT is the station code for Meerut Cantt railway station in Uttar Pradesh, India.
- 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_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. |
Created at: March 27, 2026, 1:57 p.m.