Triple
T18570185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rahul Dravid |
E453853
|
entity |
| Predicate | internationalCareerStartYear |
P41365
|
FINISHED |
| Object | 1996 |
—
|
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: 1996 | Statement: [Rahul Dravid, internationalCareerStartYear, 1996]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: internationalCareerStartYear Context triple: [Rahul Dravid, internationalCareerStartYear, 1996]
-
A.
studCareerStartYear
Indicates the calendar year in which a student's academic or educational career formally began.
-
B.
workYear
Indicates the specific year or span of years during which an entity (such as a person or organization) was engaged in work or employment.
-
C.
startedInternationalCareer
chosen
Indicates that an entity began participating at the international level in a particular field, role, or profession from a specified time.
-
D.
interviewYear
Indicates the calendar year in which an interview took place.
-
E.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53b01331c8190bec3aba40358a843 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:43 a.m.