Triple
T22147319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Five-Year Plan of India |
E547319
|
entity |
| Predicate | sectoralEmphasis |
P76324
|
FINISHED |
| Object | industry over agriculture |
—
|
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: industry over agriculture | Statement: [Second Five-Year Plan of India, sectoralEmphasis, industry over agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectoralEmphasis Context triple: [Second Five-Year Plan of India, sectoralEmphasis, industry over agriculture]
-
A.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
B.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
C.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that sector.
-
D.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
E.
hasSectoralPriority
chosen
Indicates that something is designated as having priority or special importance within a particular sector or industry.
- F. None of above.
Provenance (3 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f156988190bc9a24a37418e849 |
completed | April 28, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:33 p.m.