Triple
T22907024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make in India |
E568475
|
entity |
| Predicate | focusSectorCount |
P150183
|
FINISHED |
| Object | 25 |
—
|
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: 25 | Statement: [Make in India, focusSectorCount, 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusSectorCount Context triple: [Make in India, focusSectorCount, 25]
-
A.
sectorCountApprox
Indicates that the number of sectors involved is an approximate or estimated count rather than an exact value.
-
B.
sectorCountReferenced
Indicates that one entity specifies or refers to the number of sectors associated with another entity.
-
C.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
D.
sectorInspected
Indicates that a particular sector or area has been examined or checked, typically for compliance, safety, or condition.
-
E.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
- 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_69e2458cd9e48190943ad2e34485d939 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1801a48948190b5f51f1d02351fc7 |
completed | April 29, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69ef3b6b2e2481908258156937b5a745 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:41 p.m.