Triple
T2940647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madras College |
E79377
|
entity |
| Predicate | hasSchoolYears |
P44085
|
FINISHED |
| Object | S1 |
—
|
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: S1 | Statement: [Madras College, hasSchoolYears, S1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchoolYears Context triple: [Madras College, hasSchoolYears, S1]
-
A.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
B.
hasSchoolCategory
Indicates that an entity (such as a school or educational institution) is associated with a particular category or type of school.
-
C.
hasSchoolYearEndMonth
Indicates the month in which a school year ends for a given educational institution or system.
-
D.
hasGrades
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
-
E.
schoolAttended
Indicates that one entity has attended, or been enrolled as a student at, the school represented by the other entity.
- F. None of above. chosen
Provenance (4 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad986f38948190a636a826693a9d4f |
completed | March 8, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:56 p.m.