Triple
T11734553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Institutes of Technology |
E278990
|
entity |
| Predicate | alumniContribution |
P89630
|
FINISHED |
| Object | technology entrepreneurship |
—
|
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: technology entrepreneurship | Statement: [Indian Institutes of Technology, alumniContribution, technology entrepreneurship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alumniContribution Context triple: [Indian Institutes of Technology, alumniContribution, technology entrepreneurship]
-
A.
hasAlumniInvolvement
Indicates that an entity maintains an ongoing relationship or engagement with its former members or graduates.
-
B.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
C.
fieldAssociatedWithAlumnus
Indicates that a particular field of study, profession, or area of expertise is associated with or pursued by a given alumnus.
-
D.
hasContributionFrom
Indicates that something (such as a work, project, or outcome) is created, influenced, or supported in part by a specified contributor.
-
E.
hasProfessionalAlumni
chosen
Indicates that an institution or organization has alumni who have gone on to work in a specified profession or professional field.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4daa7f48190896fc7653e9dd70b |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.