Triple
T12760072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashoke Ganguli |
E304967
|
entity |
| Predicate | hasMajorThemeRelation |
P62989
|
FINISHED |
| Object | immigrant experience |
—
|
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: immigrant experience | Statement: [Ashoke Ganguli, hasMajorThemeRelation, immigrant experience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorThemeRelation Context triple: [Ashoke Ganguli, hasMajorThemeRelation, immigrant experience]
-
A.
majorThemeAssociation
Indicates that one entity is associated with another as a primary or central theme.
-
B.
hasThematicOrigin
Indicates that something originates from, or is thematically derived from, a particular source, subject, or theme.
-
C.
hasThematicConcern
chosen
Indicates that one entity (such as a work, text, or discourse) centrally involves, addresses, or focuses on a particular theme, issue, or subject as a primary concern.
-
D.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
E.
hasMajor
Indicates that an entity (typically a person or student) has a specific primary field of academic study or specialization.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.