Triple
T29261152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mewar State |
E741847
|
entity |
| Predicate | associatedLakeCity |
P204166
|
FINISHED |
| Object | Udaipur |
E60736
|
NE 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: Udaipur | Statement: [Mewar State, associatedLakeCity, Udaipur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLakeCity Context triple: [Mewar State, associatedLakeCity, Udaipur]
-
A.
cityOnLake
Indicates that a city is located on the shore or edge of a particular lake.
-
B.
connectsToByLake
Indicates that one entity is linked or joined to another specifically via a lake as the connecting medium or route.
-
C.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
D.
isUrbanLake
Indicates that a given lake is located within or closely associated with an urban or metropolitan area.
-
E.
locatedAcrossLakeFrom
Indicates that one entity is situated on the opposite shore of a lake relative to another entity, with the lake lying between them.
- 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_69f0912065c08190bddd23e20e8ef18e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_6a033ed9322c8190be994a8d99761caa |
completed | May 12, 2026, 2:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25d903b1f48190b49cbb4e313add38 |
completed | June 7, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_6a033df2b254819082a672859e5168e6 |
completed | May 12, 2026, 2:49 p.m. |
| PDg | Predicate description generation | batch_6a033ed880148190949a938ae2975a28 |
completed | May 12, 2026, 2:53 p.m. |
Created at: April 28, 2026, 12:41 p.m.