Triple
T36490602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Board of Governors of IIT Delhi |
E899041
|
entity |
| Predicate | hasAuthorityOver |
P544
|
FINISHED |
| Object | approval of new academic programmes at Indian Institute of Technology Delhi |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: approval of new academic programmes at Indian Institute of Technology Delhi | Statement: [Board of Governors of IIT Delhi, hasAuthorityOver, approval of new academic programmes at Indian Institute of Technology Delhi]
Provenance (2 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be26cb348190af35b00e620de9df |
completed | May 3, 2026, 9:29 p.m. |
Created at: May 3, 2026, 4:10 p.m.