Triple
T22077469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Contingency Fund of India |
E545557
|
entity |
| Predicate | initialCorpus |
P146553
|
FINISHED |
| Object | Rs 50 crore |
—
|
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: Rs 50 crore | Statement: [Contingency Fund of India, initialCorpus, Rs 50 crore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: initialCorpus Context triple: [Contingency Fund of India, initialCorpus, Rs 50 crore]
-
A.
corpus
Indicates that an entity is a collection or body of texts, documents, or linguistic data used as a unified set for analysis or reference.
-
B.
primaryCorpusType
Indicates the main or dominant type or category of corpus associated with an entity.
-
C.
hasLimitedCorpus
Indicates that the associated entity possesses only a small or restricted set of available data, texts, or examples for use or analysis.
-
D.
hasPartOfCorpus
Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
-
E.
traditionalPlacementInCorpus
Indicates the conventional or historically established position of a work or text within a larger corpus or collection.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b38844819084526372fa6c6e35 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
| PDg | Predicate description generation | batch_69e6fad59ef48190b62a2af636918a15 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:28 p.m.