Triple
T14393661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gregory Piatetsky-Shapiro |
E356903
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | ACM SIGKDD |
E13737
|
NE 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: ACM SIGKDD | Statement: [Gregory Piatetsky-Shapiro, associatedWith, ACM SIGKDD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ACM SIGKDD Context triple: [Gregory Piatetsky-Shapiro, associatedWith, ACM SIGKDD]
-
A.
SIGKDD
chosen
SIGKDD is the ACM Special Interest Group on Knowledge Discovery and Data Mining, best known for its flagship KDD conference and contributions to data mining and machine learning research.
-
B.
KDD
KDD is the commonly used abbreviation for Norway’s Ministry of Local Government and Regional Development, a government body responsible for municipal affairs, regional policy, and housing.
-
C.
IEEE International Conference on Data Mining
The IEEE International Conference on Data Mining is a leading annual research conference that focuses on advances in data mining, machine learning, and knowledge discovery in databases.
-
D.
ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data is a peer-reviewed scholarly journal published by the Association for Computing Machinery that focuses on research in data mining, knowledge discovery, and related areas of data science and machine learning.
-
E.
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering is a leading peer-reviewed journal published by the IEEE Computer Society that focuses on research in knowledge discovery, data mining, databases, and data-intensive systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de902d114881908a8f3c01b3c6d309 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94a254f881908d9494d4602064ae |
completed | May 8, 2026, 7:45 a.m. |
Created at: April 10, 2026, 1:16 a.m.