Triple
T21270906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indira Gandhi National Open University |
E524251
|
entity |
| Predicate | hasReach |
P143455
|
FINISHED |
| Object | national |
—
|
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: national | Statement: [Indira Gandhi National Open University, hasReach, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReach Context triple: [Indira Gandhi National Open University, hasReach, national]
-
A.
hasReachUnit
Indicates that one entity uses a specified unit of measurement to express its reach or extent.
-
B.
hasMet
Indicates that one entity has encountered or come into contact with another entity at least once.
-
C.
canReach
Indicates that one entity is able to access, arrive at, or establish a path to another entity.
-
D.
hasLongerReachThan
Indicates that one entity can extend, influence, or physically reach farther than another entity.
-
E.
hasHad
Indicates that an entity previously experienced, possessed, or was involved in something at some point in the past.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736534c348190a8d29e8d724dd40a |
completed | April 21, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69e5f6161dac8190b06009cd180e3ff7 |
completed | April 20, 2026, 9:47 a.m. |
| PDg | Predicate description generation | batch_69e5f9943ed881909ef49045c5bcf6df |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 4:01 p.m.