Triple
T14923640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COMBO-17 survey |
E371575
|
entity |
| Predicate | hasAnalysisType |
P116683
|
FINISHED |
| Object | statistical analysis of large samples |
—
|
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: statistical analysis of large samples | Statement: [COMBO-17 survey, hasAnalysisType, statistical analysis of large samples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAnalysisType Context triple: [COMBO-17 survey, hasAnalysisType, statistical analysis of large samples]
-
A.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
B.
hasExtractionType
Indicates that one entity is associated with a specific method, category, or mode by which something is extracted from it or through it.
-
C.
hasTaskType
Indicates that an entity is associated with or classified under a specific type or category of task.
-
D.
hasAnswerType
Indicates that a question or query is associated with a specific type or category of expected answer.
-
E.
hasFeedbackType
Indicates that an entity is associated with a specific category or type of feedback it provides or receives.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6323f8c8190af02d06352d459c3 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:34 a.m.