Triple
T11322184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalyan |
E268119
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Karjat |
E704185
|
NE FINISHED |
How this triple was built (2 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: Karjat | Statement: [Kalyan, connectedTo, Karjat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karjat Context triple: [Kalyan, connectedTo, Karjat]
-
A.
Karjat
chosen
Karjat is a town in Maharashtra, India, known as a scenic weekend getaway and trekking hub in the Western Ghats, popular for its waterfalls, forts, and proximity to Mumbai and Pune.
-
B.
Karinska
Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
-
C.
Kataja
Kataja is a short form or nickname of the female given name Katarina.
-
D.
Karkkila
Karkkila is a small town and municipality in southern Finland known for its industrial history and surrounding lakes and forests.
-
E.
Kajansi
Kajansi is a township in Uganda located near Kampala, known for its strategic position along the Kampala–Entebbe road and its local market and trading activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9dff37081909622623e66e17ccd |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543055b588190a417b3d50ade989a |
completed | April 19, 2026, 9:03 p.m. |
Created at: April 8, 2026, 9:32 p.m.