Triple
T19096800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Lucía Air Force Base |
E467426
|
entity |
| Predicate | hasIcaoCode |
P419
|
FINISHED |
| Object |
MMSM
MMSM is the ICAO airport code assigned to Santa Lucía Air Force Base in Mexico.
|
E705137
|
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: MMSM | Statement: [Santa Lucía Air Force Base, hasIcaoCode, MMSM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MMSM Context triple: [Santa Lucía Air Force Base, hasIcaoCode, MMSM]
-
A.
MMSM
MMSM is the ICAO airport code assigned to Felipe Ángeles International Airport, a major commercial airport serving the Mexico City metropolitan area.
-
B.
DMSM
The DMSM is a high-level U.S. military decoration awarded for exceptionally meritorious non-combat service in a joint duty capacity.
-
C.
MSSS
MSSS is the acronym for Quebec’s Ministry of Health and Social Services, the provincial government body responsible for overseeing public health care and social services.
-
D.
TMMMS
TMMMS is Toyota’s automobile manufacturing plant in Mississippi, known for producing vehicles such as the Toyota Corolla for the North American market.
-
E.
MSS
MSS is the Mobile Servicing System, a Canadian-built robotic arm and handling system used on the International Space Station for assembly, maintenance, and payload operations.
- 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: MMSM Triple: [Santa Lucía Air Force Base, hasIcaoCode, MMSM]
Generated description
MMSM is the ICAO airport code assigned to Santa Lucía Air Force Base in Mexico.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MMSM Target entity description: MMSM is the ICAO airport code assigned to Santa Lucía Air Force Base in Mexico.
-
A.
MMSM
chosen
MMSM is the ICAO airport code assigned to Felipe Ángeles International Airport, a major commercial airport serving the Mexico City metropolitan area.
-
B.
DMSM
The DMSM is a high-level U.S. military decoration awarded for exceptionally meritorious non-combat service in a joint duty capacity.
-
C.
MSSS
MSSS is the acronym for Quebec’s Ministry of Health and Social Services, the provincial government body responsible for overseeing public health care and social services.
-
D.
TMMMS
TMMMS is Toyota’s automobile manufacturing plant in Mississippi, known for producing vehicles such as the Toyota Corolla for the North American market.
-
E.
MSS
MSS is the Mobile Servicing System, a Canadian-built robotic arm and handling system used on the International Space Station for assembly, maintenance, and payload operations.
- F. None of above.
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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e369aeac81908913c21f4c234c8e |
completed | April 20, 2026, 8:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05dd98a1d48190bb46127c0bbc2351 |
completed | May 14, 2026, 2:35 p.m. |
| NEDg | Description generation | batch_6a05dfcf14788190a75298641ba20e0e |
completed | May 14, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05e10ae8188190a9dce95fa838ff7f |
completed | May 14, 2026, 2:49 p.m. |
Created at: April 10, 2026, 12:04 p.m.