Triple
T35047100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mala |
E1011228
|
entity |
| Predicate | nationalityAfterMigration |
P97942
|
FINISHED |
| Object | Indian immigrant in the United States |
—
|
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: Indian immigrant in the United States | Statement: [Mala, nationalityAfterMigration, Indian immigrant in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalityAfterMigration Context triple: [Mala, nationalityAfterMigration, Indian immigrant in the United States]
-
A.
nationalityAfterEmigration
chosen
Indicates the nationality a person acquires or holds after emigrating from their original country.
-
B.
emigratedAfter
Indicates that one entity emigrated from its original place at a time later than another entity’s emigration.
-
C.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
D.
immigratedTo
Indicates that an entity moved from its country of origin to live permanently in another specified country or region.
-
E.
subjectLaterNationality
Indicates that the subject’s nationality at a later point in time is the specified nationality, distinct from any earlier nationality they may have held.
- 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_69f76dcfdda48190b1ebae5da8b54f12 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: May 3, 2026, 4:01 p.m.