Triple
T14941290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markonahalli Dam |
E372534
|
entity |
| Predicate | nearPlace |
P36605
|
FINISHED |
| Object |
Kunigal
Kunigal is a town in the Tumakuru district of Karnataka, India, known for its proximity to Markonahalli Dam and its agricultural surroundings.
|
E1129815
|
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: Kunigal | Statement: [Markonahalli Dam, nearPlace, Kunigal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kunigal Context triple: [Markonahalli Dam, nearPlace, Kunigal]
-
A.
Soligalich
Soligalich is a historic Russian town known for its preserved 18th–19th century architecture and location along the Kostroma River in Kostroma Oblast.
-
B.
Kushnar
Kushnar is an alternative written form or spelling variant of the name Kushner.
-
C.
Gudia
Gudia is an Indian film directed by acclaimed filmmaker Goutam Ghose, known for its sensitive storytelling and exploration of complex social and emotional themes.
-
D.
Tarchuna
Tarchuna is the ancient Etruscan city known in Latin as Tarquinii and in modern times as Tarquinia, a major cultural and political center of Etruria in central Italy.
-
E.
Dagomys
Dagomys is a coastal resort settlement on the Black Sea in the Sochi area of Krasnodar Krai, Russia, known for its beaches and subtropical climate.
- 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: Kunigal Triple: [Markonahalli Dam, nearPlace, Kunigal]
Generated description
Kunigal is a town in the Tumakuru district of Karnataka, India, known for its proximity to Markonahalli Dam and its agricultural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kunigal Target entity description: Kunigal is a town in the Tumakuru district of Karnataka, India, known for its proximity to Markonahalli Dam and its agricultural surroundings.
-
A.
Soligalich
Soligalich is a historic Russian town known for its preserved 18th–19th century architecture and location along the Kostroma River in Kostroma Oblast.
-
B.
Kushnar
Kushnar is an alternative written form or spelling variant of the name Kushner.
-
C.
Gudia
Gudia is an Indian film directed by acclaimed filmmaker Goutam Ghose, known for its sensitive storytelling and exploration of complex social and emotional themes.
-
D.
Tarchuna
Tarchuna is the ancient Etruscan city known in Latin as Tarquinii and in modern times as Tarquinia, a major cultural and political center of Etruria in central Italy.
-
E.
Dagomys
Dagomys is a coastal resort settlement on the Black Sea in the Sochi area of Krasnodar Krai, Russia, known for its beaches and subtropical climate.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64a2f24819099b21566756668a2 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bd69df481908d8b1a5e6add0a7b |
completed | May 9, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_69fe8c6dc58c819096551e9f48abf2f6 |
completed | May 9, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe901a32a48190a8b523f02804922c |
completed | May 9, 2026, 1:38 a.m. |
Created at: April 10, 2026, 2:38 a.m.