Triple
T23151319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaugada |
E578329
|
entity |
| Predicate | sharesEdictSeriesWith |
P151122
|
FINISHED |
| Object |
Kalsi
Kalsi is an archaeological site in Uttarakhand, India, best known for its rock edicts of the Mauryan emperor Ashoka inscribed on a large quartz rock.
|
E1573666
|
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: Kalsi | Statement: [Jaugada, sharesEdictSeriesWith, Kalsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalsi Context triple: [Jaugada, sharesEdictSeriesWith, Kalsi]
-
A.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
B.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
-
C.
Klyntar
Klyntar are an alien symbiote species in Marvel Comics known for bonding with hosts to enhance their abilities while often exerting a corrupting influence.
-
D.
Kalyar
Kalyar is a notable Sufi pilgrimage town in India associated with the Chishti Order and revered for its prominent dargah (shrine).
-
E.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
- 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: Kalsi Triple: [Jaugada, sharesEdictSeriesWith, Kalsi]
Generated description
Kalsi is an archaeological site in Uttarakhand, India, best known for its rock edicts of the Mauryan emperor Ashoka inscribed on a large quartz rock.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kalsi Target entity description: Kalsi is an archaeological site in Uttarakhand, India, best known for its rock edicts of the Mauryan emperor Ashoka inscribed on a large quartz rock.
-
A.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
B.
Karesi
Karesi is a central district and municipality of Balıkesir in western Turkey, known for its role as an administrative and commercial hub of the province.
-
C.
Klyntar
Klyntar are an alien symbiote species in Marvel Comics known for bonding with hosts to enhance their abilities while often exerting a corrupting influence.
-
D.
Kalyar
Kalyar is a notable Sufi pilgrimage town in India associated with the Chishti Order and revered for its prominent dargah (shrine).
-
E.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ef982488190984a6358bdcd577c |
completed | April 29, 2026, 4:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3098168481908aa4e4a985314db1 |
completed | May 19, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_6a0c3442ccb08190aaea6fe426a3dd10 |
completed | May 19, 2026, 9:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c34a421308190bbaf614cdfa5e146 |
completed | May 19, 2026, 10 a.m. |
Created at: April 17, 2026, 4:01 p.m.