Triple
T14259030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranga Reddy district |
E353461
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Vikarabad
Vikarabad is a town in the Indian state of Telangana known for its nearby Ananthagiri Hills, a popular hill station and trekking destination.
|
E1094135
|
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: Vikarabad | Statement: [Ranga Reddy district, hasCity, Vikarabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vikarabad Context triple: [Ranga Reddy district, hasCity, Vikarabad]
-
A.
Nasirabad
Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
-
B.
Nasirabad
Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
-
C.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
-
D.
Khairatabad
Khairatabad is a prominent commercial and administrative locality in central Hyderabad, India, known for its major government offices, busy junction, and proximity to key city landmarks.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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: Vikarabad Triple: [Ranga Reddy district, hasCity, Vikarabad]
Generated description
Vikarabad is a town in the Indian state of Telangana known for its nearby Ananthagiri Hills, a popular hill station and trekking destination.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vikarabad Target entity description: Vikarabad is a town in the Indian state of Telangana known for its nearby Ananthagiri Hills, a popular hill station and trekking destination.
-
A.
Nasirabad
Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
-
B.
Nasirabad
Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
-
C.
Shamshabad
Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
-
D.
Khairatabad
Khairatabad is a prominent commercial and administrative locality in central Hyderabad, India, known for its major government offices, busy junction, and proximity to key city landmarks.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6352611c819090d062fe3079cd03 |
completed | April 14, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd467b8300819091454dfa36ec2a9d |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd484d079081908c6a69180ee5d29b |
completed | May 8, 2026, 2:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd48c8c0e48190afb2f121362a7a76 |
completed | May 8, 2026, 2:22 a.m. |
Created at: April 10, 2026, 1:09 a.m.