Triple
T4872034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NH 44 |
E109106
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object |
Kamareddy
Kamareddy is a town in the Indian state of Telangana known as a regional commercial and transportation hub.
|
E476036
|
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: Kamareddy | Statement: [NH 44, connectsCity, Kamareddy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamareddy Context triple: [NH 44, connectsCity, Kamareddy]
-
A.
Raja Gangadhar Rao
Raja Gangadhar Rao was the Maharaja of Jhansi and husband of Rani Lakshmibai, playing a key role in the events leading up to the Indian Rebellion of 1857.
-
B.
Satyavedu
Satyavedu is a town in the Tirupati district of Andhra Pradesh, India, known for its agricultural surroundings and proximity to the Tamil Nadu border.
-
C.
Suryanarayana
Suryanarayana is a benevolent healing form of the Hindu sun god Surya, revered for restoring health and vitality.
-
D.
Muddu Krishna
Muddu Krishna is a celebrated Kannada literary work by poet D. R. Bendre, known for its lyrical exploration of devotion and human emotion.
-
E.
Tenali Ramakrishna
Tenali Ramakrishna was a legendary 16th-century Telugu poet and jester famed for his wit, intelligence, and humorous folktales in the court of the Vijayanagara Empire.
- 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: Kamareddy Triple: [NH 44, connectsCity, Kamareddy]
Generated description
Kamareddy is a town in the Indian state of Telangana known as a regional commercial and transportation hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kamareddy Target entity description: Kamareddy is a town in the Indian state of Telangana known as a regional commercial and transportation hub.
-
A.
Raja Gangadhar Rao
Raja Gangadhar Rao was the Maharaja of Jhansi and husband of Rani Lakshmibai, playing a key role in the events leading up to the Indian Rebellion of 1857.
-
B.
Satyavedu
Satyavedu is a town in the Tirupati district of Andhra Pradesh, India, known for its agricultural surroundings and proximity to the Tamil Nadu border.
-
C.
Suryanarayana
Suryanarayana is a benevolent healing form of the Hindu sun god Surya, revered for restoring health and vitality.
-
D.
Muddu Krishna
Muddu Krishna is a celebrated Kannada literary work by poet D. R. Bendre, known for its lyrical exploration of devotion and human emotion.
-
E.
Tenali Ramakrishna
Tenali Ramakrishna was a legendary 16th-century Telugu poet and jester famed for his wit, intelligence, and humorous folktales in the court of the Vijayanagara Empire.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d9e27908190a0c4540ee2559c4b |
completed | March 20, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67f1ca1881909a7412087fa0efab |
completed | March 21, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69be68b9300c8190ba829be08e520047 |
completed | March 21, 2026, 9:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be6961d8688190a041e476e082ac36 |
completed | March 21, 2026, 9:48 a.m. |
Created at: March 20, 2026, 1:27 p.m.