Triple
T13895844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayubia |
E334084
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object |
Dunga Gali
Dunga Gali is a hill station and tourist resort in Pakistan’s Galyat region, known for its cool climate, pine forests, and colonial-era charm.
|
E1068729
|
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: Dunga Gali | Statement: [Ayubia, nearbyPlace, Dunga Gali]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dunga Gali Context triple: [Ayubia, nearbyPlace, Dunga Gali]
-
A.
Bara Gali
Bara Gali is a small mountain resort town in Pakistan’s Galiyat region, known for its cool climate, forested hills, and scenic hiking opportunities.
-
B.
Ghagga
Ghagga is a small town in the Patiala district of Punjab, India, known for its agrarian surroundings and local market activities.
-
C.
Dargai
Dargai is a town in Pakistan’s Khyber Pakhtunkhwa province, historically known as a strategic and military site in the Malakand region.
-
D.
Banshiwala
Banshiwala is a Bengali novel by acclaimed writer Shirshendu Mukhopadhyay, known for its evocative storytelling and exploration of human relationships.
-
E.
Bhokar
Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
- 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: Dunga Gali Triple: [Ayubia, nearbyPlace, Dunga Gali]
Generated description
Dunga Gali is a hill station and tourist resort in Pakistan’s Galyat region, known for its cool climate, pine forests, and colonial-era charm.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dunga Gali Target entity description: Dunga Gali is a hill station and tourist resort in Pakistan’s Galyat region, known for its cool climate, pine forests, and colonial-era charm.
-
A.
Bara Gali
Bara Gali is a small mountain resort town in Pakistan’s Galiyat region, known for its cool climate, forested hills, and scenic hiking opportunities.
-
B.
Ghagga
Ghagga is a small town in the Patiala district of Punjab, India, known for its agrarian surroundings and local market activities.
-
C.
Dargai
Dargai is a town in Pakistan’s Khyber Pakhtunkhwa province, historically known as a strategic and military site in the Malakand region.
-
D.
Banshiwala
Banshiwala is a Bengali novel by acclaimed writer Shirshendu Mukhopadhyay, known for its evocative storytelling and exploration of human relationships.
-
E.
Bhokar
Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25d72c6c819093bf9c43136839d4 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71eb1808190b0a3a28a8011e9c7 |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c868bdfc8190a13379363d01568d |
completed | May 3, 2026, 10:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c9732d188190a8a7151d21e0a310 |
completed | May 3, 2026, 10:17 p.m. |
Created at: April 9, 2026, 10:15 p.m.