Triple
T22146892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eknath Solkar |
E547308
|
entity |
| Predicate | tookCatchesInTests |
P147163
|
FINISHED |
| Object | over 50 |
—
|
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: over 50 | Statement: [Eknath Solkar, tookCatchesInTests, over 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookCatchesInTests Context triple: [Eknath Solkar, tookCatchesInTests, over 50]
-
A.
catches
Indicates that one entity successfully seizes, intercepts, or takes hold of another entity, often stopping its motion or preventing its escape.
-
B.
testsIn
Indicates that one entity conducts or performs tests within, on, or using another entity.
-
C.
testedInCase
Indicates that something (such as a method, component, or behavior) is exercised or verified within a particular test case.
-
D.
canBeCaughtWith
Indicates that one entity is capable of being captured, obtained, or discovered using another specified entity or method.
-
E.
oftenTriesToCatch
Indicates that one entity frequently attempts to catch, capture, or seize another 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f156988190bc9a24a37418e849 |
completed | April 28, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69e71b384e008190b723c9a0f1089d66 |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:33 p.m.