Triple
T6022492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Fahd International Airport |
E134096
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
DMM
DMM is the IATA airport code for King Fahd International Airport, the major international airport serving the Dammam region in Saudi Arabia.
|
E560904
|
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: DMM | Statement: [King Fahd International Airport, IATAcode, DMM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DMM Context triple: [King Fahd International Airport, IATAcode, DMM]
-
A.
DMM
DMM is the United States Postal Service’s Domestic Mail Manual, which sets the official standards and regulations for mailing within the United States.
-
B.
Dragon Mart
Dragon Mart is a massive Chinese-themed retail and trading complex in Dubai, known as one of the largest hubs for Chinese products outside mainland China.
-
C.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
D.
Daruma Market
Daruma Market is a traditional Japanese fair in Takasaki famous for its sale of daruma dolls, which are used as good-luck charms and symbols of perseverance.
-
E.
Akihabara
Akihabara is a famous Tokyo district known as a major center for electronics, anime, manga, and otaku culture.
- 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: DMM Triple: [King Fahd International Airport, IATAcode, DMM]
Generated description
DMM is the IATA airport code for King Fahd International Airport, the major international airport serving the Dammam region in Saudi Arabia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DMM Target entity description: DMM is the IATA airport code for King Fahd International Airport, the major international airport serving the Dammam region in Saudi Arabia.
-
A.
DMM
DMM is the United States Postal Service’s Domestic Mail Manual, which sets the official standards and regulations for mailing within the United States.
-
B.
Dragon Mart
Dragon Mart is a massive Chinese-themed retail and trading complex in Dubai, known as one of the largest hubs for Chinese products outside mainland China.
-
C.
Shibuya 109
Shibuya 109 is a famous multi-story fashion shopping mall in Tokyo known as a trendsetting hub for youth and street fashion.
-
D.
Daruma Market
Daruma Market is a traditional Japanese fair in Takasaki famous for its sale of daruma dolls, which are used as good-luck charms and symbols of perseverance.
-
E.
Akihabara
Akihabara is a famous Tokyo district known as a major center for electronics, anime, manga, and otaku culture.
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fbbf03c8190baf449a5d393af5c |
completed | March 22, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c108c2e1c88190a1629c6438f6c8bd |
completed | March 23, 2026, 9:32 a.m. |
| NEDg | Description generation | batch_69c1096d5f2881909126730848ca0e78 |
completed | March 23, 2026, 9:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10b2699088190a468989beded758e |
completed | March 23, 2026, 9:43 a.m. |
Created at: March 22, 2026, 4:07 p.m.