Triple
T15648226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banaskantha district |
E376236
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Kankrej
Kankrej is a town in Gujarat, India, known primarily as an agricultural center and for lending its name to the hardy Kankrej breed of cattle.
|
E1169435
|
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: Kankrej | Statement: [Banaskantha district, hasTown, Kankrej]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kankrej Context triple: [Banaskantha district, hasTown, Kankrej]
-
A.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
-
B.
Jalesar
Jalesar is a town in the Braj cultural region of northern India, known for its traditional brassware and temple heritage.
-
C.
Moglina
Moglina is a Slavic-origin surname, most notably borne by individuals such as Nina Moglina.
-
D.
Kundla
Kundla is a surname most notably associated with John Kundla, the Hall of Fame head coach who led the Minneapolis Lakers to multiple early NBA championships.
-
E.
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.
- 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: Kankrej Triple: [Banaskantha district, hasTown, Kankrej]
Generated description
Kankrej is a town in Gujarat, India, known primarily as an agricultural center and for lending its name to the hardy Kankrej breed of cattle.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kankrej Target entity description: Kankrej is a town in Gujarat, India, known primarily as an agricultural center and for lending its name to the hardy Kankrej breed of cattle.
-
A.
Vishkanya
Vishkanya is a 1991 Indian Hindi-language horror film known for its supernatural revenge plot and early appearance of actress Riya Sen.
-
B.
Jalesar
Jalesar is a town in the Braj cultural region of northern India, known for its traditional brassware and temple heritage.
-
C.
Moglina
Moglina is a Slavic-origin surname, most notably borne by individuals such as Nina Moglina.
-
D.
Kundla
Kundla is a surname most notably associated with John Kundla, the Hall of Fame head coach who led the Minneapolis Lakers to multiple early NBA championships.
-
E.
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.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed7212c8190be6ff76afa25f7ca |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67936e388190913c9060194e5b53 |
completed | May 9, 2026, 4:57 p.m. |
| NEDg | Description generation | batch_69ff6883b5048190b64e4361bc89dd80 |
completed | May 9, 2026, 5:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6911a76c819088c8a86d2106b6c6 |
completed | May 9, 2026, 5:04 p.m. |
Created at: April 10, 2026, 4:15 a.m.