Triple
T19669656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Central Railway |
E472298
|
entity |
| Predicate | hasWorkshop |
P42933
|
FINISHED |
| Object |
Kota coaching depot
Kota coaching depot is a major railway coach maintenance and servicing facility located in Kota, Rajasthan, under the jurisdiction of Indian Railways.
|
E1389582
|
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: Kota coaching depot | Statement: [West Central Railway, hasWorkshop, Kota coaching depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kota coaching depot Context triple: [West Central Railway, hasWorkshop, Kota coaching depot]
-
A.
Kota coaching hub
Kota coaching hub is a major educational center in Rajasthan renowned for its large concentration of coaching institutes that prepare students for competitive engineering and medical entrance exams.
-
B.
Dinas depot
Dinas depot is a maintenance and storage facility serving the Welsh Highland Railway in North Wales.
-
C.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
D.
Peenya depot
Peenya depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system.
-
E.
Kajang Depot
Kajang Depot is a major maintenance and operations facility serving Malaysia’s MRT Kajang Line in the Greater Kuala Lumpur area.
- 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: Kota coaching depot Triple: [West Central Railway, hasWorkshop, Kota coaching depot]
Generated description
Kota coaching depot is a major railway coach maintenance and servicing facility located in Kota, Rajasthan, under the jurisdiction of Indian Railways.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kota coaching depot Target entity description: Kota coaching depot is a major railway coach maintenance and servicing facility located in Kota, Rajasthan, under the jurisdiction of Indian Railways.
-
A.
Kota coaching hub
Kota coaching hub is a major educational center in Rajasthan renowned for its large concentration of coaching institutes that prepare students for competitive engineering and medical entrance exams.
-
B.
Dinas depot
Dinas depot is a maintenance and storage facility serving the Welsh Highland Railway in North Wales.
-
C.
Pajura depot
Pajura depot is a maintenance and storage facility serving the Bucharest Metro system in Romania.
-
D.
Peenya depot
Peenya depot is a major maintenance and stabling facility serving Bengaluru’s Namma Metro system.
-
E.
Kajang Depot
Kajang Depot is a major maintenance and operations facility serving Malaysia’s MRT Kajang Line in the Greater Kuala Lumpur area.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416ad1b481908d2890d8c21aac5c |
completed | April 20, 2026, 3:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0787bcb6048190a46594a843c9c468 |
completed | May 15, 2026, 8:53 p.m. |
| NEDg | Description generation | batch_6a0788d73c7081909e61cfda754c6a57 |
completed | May 15, 2026, 8:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0789848cc88190bb8b0109cede2275 |
completed | May 15, 2026, 9 p.m. |
Created at: April 10, 2026, 1:45 p.m.