Triple
T34704445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agra–Jaipur route |
E1000461
|
entity |
| Predicate | languageUsedAtStations |
P202399
|
FINISHED |
| Object | Hindi |
—
|
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: Hindi | Statement: [Agra–Jaipur route, languageUsedAtStations, Hindi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAtStations Context triple: [Agra–Jaipur route, languageUsedAtStations, Hindi]
-
A.
hasLanguageVariantsAtStation
Indicates that a station supports multiple language variants for its information, services, or interfaces.
-
B.
countryStationed
Indicates that an entity is assigned, based, or deployed within the territory of a specified country.
-
C.
isSpokenOn
Indicates that a particular language, phrase, or utterance is used or occurs during a specified time, event, or occasion.
-
D.
sharesStationsWith
Indicates that two transit routes or lines have one or more stations or stops in common along their paths.
-
E.
nearbyCountryStation
Indicates that a station is located in a country that is geographically close to or bordering the reference country.
- F. None of above. chosen
Provenance (4 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a0079e152648190a9da2add94fc1831 |
completed | May 10, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_6a0078f77f9c8190af357a6016a2bd53 |
completed | May 10, 2026, 12:24 p.m. |
| PDg | Predicate description generation | batch_6a0079e0a9688190a420759fafd47807 |
completed | May 10, 2026, 12:28 p.m. |
Created at: May 3, 2026, 3:59 p.m.