Triple
T15406418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taunggyi |
E368467
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Heho Airport
Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
|
E1164159
|
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: Heho Airport | Statement: [Taunggyi, near, Heho Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heho Airport Context triple: [Taunggyi, near, Heho Airport]
-
A.
Whyalla Airport
Whyalla Airport is a regional airport in South Australia that serves the city of Whyalla with domestic flights and general aviation services.
-
B.
Muanda Airport
Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
-
C.
Kadala Airport
Kadala Airport is the main commercial airport serving the city of Chita in eastern Siberia, Russia.
-
D.
Beni Airport
Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
-
E.
Baljek Airport
Baljek Airport is a small regional airport serving the town of Tura and the surrounding Garo Hills region in the Indian state of Meghalaya.
- 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: Heho Airport Triple: [Taunggyi, near, Heho Airport]
Generated description
Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heho Airport Target entity description: Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
-
A.
Whyalla Airport
Whyalla Airport is a regional airport in South Australia that serves the city of Whyalla with domestic flights and general aviation services.
-
B.
Muanda Airport
Muanda Airport is a public airport serving the coastal town of Muanda in the western Democratic Republic of the Congo, providing regional air connectivity for passengers and cargo.
-
C.
Kadala Airport
Kadala Airport is the main commercial airport serving the city of Chita in eastern Siberia, Russia.
-
D.
Beni Airport
Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
-
E.
Baljek Airport
Baljek Airport is a small regional airport serving the town of Tura and the surrounding Garo Hills region in the Indian state of Meghalaya.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ea36c6881909eaea48e9608897a |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4546959081909f94449c0028ca3e |
completed | May 9, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69ff49541fcc8190a1d22721bc255e19 |
completed | May 9, 2026, 2:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff49f6db508190b0127a59d332512e |
completed | May 9, 2026, 2:51 p.m. |
Created at: April 10, 2026, 3:20 a.m.