Triple
T26226174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jal Marg Vikas Project |
E655897
|
entity |
| Predicate | multimodalTerminalLocation |
P160536
|
FINISHED |
| Object | Sahibganj |
—
|
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: Sahibganj | Statement: [Jal Marg Vikas Project, multimodalTerminalLocation, Sahibganj]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multimodalTerminalLocation Context triple: [Jal Marg Vikas Project, multimodalTerminalLocation, Sahibganj]
-
A.
multimodalTerminalLocation
chosen
Indicates the location where multiple modes of transportation converge or are accessible within a single terminal or hub.
-
B.
nearbyAirportTerminal
Indicates that one airport terminal is located close to another airport terminal in physical space.
-
C.
passengerTerminalType
Indicates the specific kind or category of passenger terminal associated with an entity.
-
D.
stationComplex
Indicates a relationship where one entity is a station complex that encompasses or is associated with another station-related entity.
-
E.
otherMajorTerminal
Indicates that an entity is associated with a different primary terminal or endpoint than the one currently referenced or considered.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d53d94081909d0ae8f05e8de84c |
completed | May 2, 2026, 2:42 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 8:58 p.m.