Triple
T15207870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bidhya Devi Bhandari |
E363435
|
entity |
| Predicate | politicalCareerStart |
P21425
|
FINISHED |
| Object | student politics in the 1970s |
—
|
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: student politics in the 1970s | Statement: [Bidhya Devi Bhandari, politicalCareerStart, student politics in the 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: politicalCareerStart Context triple: [Bidhya Devi Bhandari, politicalCareerStart, student politics in the 1970s]
-
A.
startTimeOfPoliticalCareer
chosen
Indicates the point in time when an individual’s political career officially began.
-
B.
politicalActivityStart
Indicates the point in time when an entity begins engaging in a specified political activity or role.
-
C.
candidacyStartDate
Indicates the date on which an entity’s candidacy for a role, position, or election officially begins.
-
D.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
E.
termStartAsStateRepresentative
Indicates the date or event when an individual begins serving in office as a state representative.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b8e2788190bd1831762e4181ae |
completed | April 15, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69deb97ee9d881908711dbe12a55283c |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:11 a.m.