Triple
T16681640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Entry Scheme |
E405353
|
entity |
| Predicate | locationOfSelection |
P124231
|
FINISHED |
| Object | university and engineering college campuses across India |
—
|
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: university and engineering college campuses across India | Statement: [University Entry Scheme, locationOfSelection, university and engineering college campuses across India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfSelection Context triple: [University Entry Scheme, locationOfSelection, university and engineering college campuses across India]
-
A.
locationInDocument
Indicates that one entity specifies where another entity is situated or referenced within a document.
-
B.
uiLocation
Indicates the on-screen position or placement of a user interface element within a UI layout or display.
-
C.
textLocation
Indicates the spatial or positional relationship of a piece of text within a larger document, page, or layout.
-
D.
locationInSystem
Indicates that one entity is situated within or belongs to the spatial or organizational bounds of a particular system.
-
E.
locationOfMark
Indicates that one entity is the place or position where a particular mark is found or applied.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d7018448190b3cb23191322044e |
completed | April 18, 2026, 12:47 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.