Triple
T122428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIG |
E2477
|
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: [SIG, associatedWith, ACM SIGKDD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ACM SIGKDD Context triple: [SIG, 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.
SIGIR
SIGIR is a leading ACM Special Interest Group focused on advancing research and development in information retrieval and search technologies.
-
C.
ACM SIGSPATIAL
ACM SIGSPATIAL is a Special Interest Group of the Association for Computing Machinery focused on research and development in spatial and geographic information systems.
-
D.
SIGMOD
SIGMOD is a leading ACM special interest group focused on the research and development of data management and database systems.
-
E.
ACM Digital Library
The ACM Digital Library is a comprehensive online research repository providing access to the Association for Computing Machinery’s journals, conference proceedings, technical magazines, and other computing-related publications.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a2573b4e7481909ee09d2899f8a74b |
completed | Feb. 28, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a29e494ef08190b8c5b5f8d52251c8 |
completed | Feb. 28, 2026, 7:50 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.