Triple
T25825626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhopal Junction railway station |
E650521
|
entity |
| Predicate | connectsToCityArea |
P112428
|
FINISHED |
| Object | Old Bhopal |
—
|
NE NERFINISHED |
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: Old Bhopal | Statement: [Bhopal Junction railway station, connectsToCityArea, Old Bhopal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToCityArea Context triple: [Bhopal Junction railway station, connectsToCityArea, Old Bhopal]
-
A.
connectsToAreaKnownFor
Indicates that something has a direct link or association to a specific area that is recognized or notable for certain characteristics or features.
-
B.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
C.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
D.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
E.
hasAreaConnections
chosen
Indicates that an entity is linked to one or more surrounding or related areas, typically representing spatial or regional connections between them.
- F. None of above.
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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6cee45590819086e489bfccbe4ac3 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
Created at: April 22, 2026, 7:36 a.m.