Triple
T3780354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narendra Modi Stadium |
E85400
|
entity |
| Predicate | reconstructionCost |
P51456
|
FINISHED |
| Object | approximately 800 crore INR |
—
|
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: approximately 800 crore INR | Statement: [Narendra Modi Stadium, reconstructionCost, approximately 800 crore INR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reconstructionCost Context triple: [Narendra Modi Stadium, reconstructionCost, approximately 800 crore INR]
-
A.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
-
B.
numberOfReconstructions
Indicates the count of times an entity has been reconstructed or rebuilt.
-
C.
reconstructionFeature
Indicates that one entity serves as a feature, component, or characteristic used in the reconstruction or restoration of another entity.
-
D.
reconstructedIn
Indicates that something has been rebuilt, restored, or re-created within a particular context, location, or medium.
-
E.
reconstructionFor
Indicates that one entity serves as a reconstruction, restoration, or rebuilt version of another entity.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
| PDg | Predicate description generation | batch_69aee633dab88190b14cec8afb19ca6a |
completed | March 9, 2026, 3:24 p.m. |
Created at: March 9, 2026, 3:12 p.m.