Triple
T1522388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mae Sot |
E32257
|
entity |
| Predicate | airportIATAcode |
P418
|
FINISHED |
| Object |
MAQ
MAQ is the IATA airport code for Mae Sot Airport, which serves the town of Mae Sot in western Thailand near the Myanmar border.
|
E173883
|
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: MAQ | Statement: [Mae Sot, airportIATAcode, MAQ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAQ Context triple: [Mae Sot, airportIATAcode, MAQ]
-
A.
MAB
MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
-
B.
MWAK Company
MWAK Company was a major construction consortium responsible for building the Grand Coulee Dam, one of the largest concrete structures and hydroelectric power projects in the United States.
-
C.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
D.
Meraki
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
-
E.
MSA
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
- 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: MAQ Triple: [Mae Sot, airportIATAcode, MAQ]
Generated description
MAQ is the IATA airport code for Mae Sot Airport, which serves the town of Mae Sot in western Thailand near the Myanmar border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MAQ Target entity description: MAQ is the IATA airport code for Mae Sot Airport, which serves the town of Mae Sot in western Thailand near the Myanmar border.
-
A.
MAB
MAB is a German bibliographic data format used for cataloging and exchanging library records, closely related to and historically aligned with MARC standards.
-
B.
MWAK Company
MWAK Company was a major construction consortium responsible for building the Grand Coulee Dam, one of the largest concrete structures and hydroelectric power projects in the United States.
-
C.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
D.
Meraki
Meraki is a cloud-managed IT company known for its wireless, switching, security, and device management solutions, acquired by and operating as a subsidiary of Cisco.
-
E.
MSA
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907fe8b0c8190a765afd3a10ee5e0 |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad294f9e2481909f1d685d7f083c6a |
completed | March 8, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69ad29f4edc48190b78a6df091e289ab |
completed | March 8, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2a78b9608190b70f8d0ae531618d |
completed | March 8, 2026, 7:51 a.m. |
Created at: March 4, 2026, 7:26 p.m.