Triple
T2780499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tijuana International Airport |
E61680
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object | MMTJ |
E61680
|
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: MMTJ | Statement: [Tijuana International Airport, ICAOCode, MMTJ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MMTJ Context triple: [Tijuana International Airport, ICAOCode, MMTJ]
-
A.
MMTJ
chosen
MMTJ is the ICAO airport code for Tijuana International Airport, a major commercial airport serving Tijuana in Baja California, Mexico.
-
B.
MTT
MTT is the acronym for Cuba’s Territorial Troops Militia, a large volunteer defense force integrated into the country’s national defense system.
-
C.
MTD
MTD is the public bus transit agency serving the Champaign–Urbana metropolitan area in Illinois.
-
D.
MTPD
MTPD is the law enforcement agency responsible for policing the Washington Metropolitan Area Transit Authority’s transit system, including Metrorail and Metrobus.
-
E.
MJ
MJ is the widely used nickname for Michael Jordan, the legendary American basketball player often regarded as the greatest in NBA history.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd997ebc8190bff88fe549827615 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc05cf84881908e771471dbda4c8d |
completed | March 10, 2026, 6:55 a.m. |
Created at: March 6, 2026, 9:57 p.m.