Triple
T12335925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maguindanao |
E294084
|
entity |
| Predicate | hasAirport |
P105
|
FINISHED |
| Object |
Awang Airport
Awang Airport is a domestic airport serving the province of Maguindanao in the southern Philippines.
|
E993440
|
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: Awang Airport | Statement: [Maguindanao, hasAirport, Awang Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Awang Airport Context triple: [Maguindanao, hasAirport, Awang Airport]
-
A.
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.
-
B.
Dumatubin Airport
Dumatubin Airport is a small regional airport serving the Kai Islands in Indonesia, providing domestic air connections to this remote archipelago.
-
C.
Begumpet Airport
Begumpet Airport is the former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
-
D.
Diffa Airport
Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
-
E.
Naga Airport
Naga Airport is a domestic airport serving the city of Naga and surrounding areas in the Bicol Region of the Philippines.
- 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: Awang Airport Triple: [Maguindanao, hasAirport, Awang Airport]
Generated description
Awang Airport is a domestic airport serving the province of Maguindanao in the southern Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Awang Airport Target entity description: Awang Airport is a domestic airport serving the province of Maguindanao in the southern Philippines.
-
A.
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.
-
B.
Dumatubin Airport
Dumatubin Airport is a small regional airport serving the Kai Islands in Indonesia, providing domestic air connections to this remote archipelago.
-
C.
Begumpet Airport
Begumpet Airport is the former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
-
D.
Diffa Airport
Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
-
E.
Naga Airport
Naga Airport is a domestic airport serving the city of Naga and surrounding areas in the Bicol Region of the Philippines.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f6683e881908920e1fee02a14e3 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea0a4c4819091a7a66c3b73d776 |
completed | May 2, 2026, 8:29 p.m. |
| NEDg | Description generation | batch_69f65fadc97081908376913e390cfc3d |
completed | May 2, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f660c3d914819097b57784889ca389 |
completed | May 2, 2026, 8:38 p.m. |
Created at: April 8, 2026, 9:53 p.m.