Triple
T8654706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilaspur |
E205384
|
entity |
| Predicate | hasRailwayCode |
P18202
|
FINISHED |
| Object |
BSP
BSP is the Indian Railways station code for Bilaspur Junction, a major railway hub in Chhattisgarh, India.
|
E749904
|
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: BSP | Statement: [Bilaspur, hasRailwayCode, BSP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BSP Context triple: [Bilaspur, hasRailwayCode, BSP]
-
A.
BSP
BSP is the main social-democratic political party in Bulgaria and one of the country’s oldest and largest political organizations.
-
B.
BSP
BSP is an acronym used by the International Air Transport Association (IATA) for its Billing and Settlement Plan, a system that streamlines financial transactions between travel agents and airlines.
-
C.
BSP
BSP is the Bangko Sentral ng Pilipinas, the central bank of the Philippines responsible for monetary policy, financial stability, and currency issuance.
-
D.
SBSP
SBSP is the ICAO airport code for Congonhas–São Paulo Airport, a major domestic airport serving the city of São Paulo, Brazil.
-
E.
PBSP
PBSP is a maximum-security California state prison in Crescent City known for housing some of the state’s most dangerous inmates and operating extensive Security Housing Units.
- 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: BSP Triple: [Bilaspur, hasRailwayCode, BSP]
Generated description
BSP is the Indian Railways station code for Bilaspur Junction, a major railway hub in Chhattisgarh, India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BSP Target entity description: BSP is the Indian Railways station code for Bilaspur Junction, a major railway hub in Chhattisgarh, India.
-
A.
BSP
BSP is an acronym used by the International Air Transport Association (IATA) for its Billing and Settlement Plan, a system that streamlines financial transactions between travel agents and airlines.
-
B.
BSP
BSP is the Bangko Sentral ng Pilipinas, the central bank of the Philippines responsible for monetary policy, financial stability, and currency issuance.
-
C.
BSP
BSP is the main social-democratic political party in Bulgaria and one of the country’s oldest and largest political organizations.
-
D.
SBSP
SBSP is the ICAO airport code for Congonhas–São Paulo Airport, a major domestic airport serving the city of São Paulo, Brazil.
-
E.
PBSP
PBSP is a maximum-security California state prison in Crescent City known for housing some of the state’s most dangerous inmates and operating extensive Security Housing Units.
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48432568819093b9a867b4f62b78 |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccdaad2881908f131ee9da2841d1 |
completed | April 2, 2026, 8:08 p.m. |
| NEDg | Description generation | batch_69cecf69fdb4819098a8af4e26354fea |
completed | April 2, 2026, 8:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ced06cfce88190ad4b95f1aa82d42b |
completed | April 2, 2026, 8:24 p.m. |
Created at: March 30, 2026, 6:29 p.m.