Triple
T7934497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hack |
E184254
|
entity |
| Predicate | hasTypeChecker |
P79862
|
FINISHED |
| Object | Hack typechecker |
—
|
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: Hack typechecker | Statement: [Hack, hasTypeChecker, Hack typechecker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeChecker Context triple: [Hack, hasTypeChecker, Hack typechecker]
-
A.
hasTypeSystem
Indicates that an entity employs, is governed by, or is associated with a particular type system (a defined set of rules for classifying and constraining types).
-
B.
hasCheckpointType
Indicates that a checkpoint is associated with a specific type or category defining its role or characteristics.
-
C.
hasCriterionType
Indicates that something is associated with or classified by a specific type of criterion used for evaluation or decision-making.
-
D.
hasRuntimeType
Indicates that an entity is of, or conforms to, a specific type when evaluated at runtime rather than at compile time.
-
E.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aeb132c8190bea4906aaf51b869 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:08 p.m.