Triple
T8760962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhilai |
E208195
|
entity |
| Predicate | transportByRail |
P71547
|
FINISHED |
| Object | served by Durg railway station |
—
|
LITERAL 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: served by Durg railway station | Statement: [Bhilai, transportByRail, served by Durg railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportByRail Context triple: [Bhilai, transportByRail, served by Durg railway station]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
hasRailRoute
Indicates that there exists a rail-based transportation route or connection between the related entities.
-
C.
hasPassengerRailConnection
chosen
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
D.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
countryRailConnection
Indicates that there is a railway connection or service linking two countries.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5df9729481908679151988b76d2f |
completed | March 31, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:40 p.m.