Triple
T122422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIG |
E2477
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | ACM SIGMOD |
E13733
|
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 SIGMOD | Statement: [SIG, associatedWith, ACM SIGMOD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ACM SIGMOD Context triple: [SIG, associatedWith, ACM SIGMOD]
-
A.
SIGMOD
chosen
SIGMOD is a leading ACM special interest group focused on the research and development of data management and database systems.
-
B.
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.
-
C.
ACM Transactions series
The ACM Transactions series is a collection of peer-reviewed scholarly journals published by the Association for Computing Machinery, each focusing on a specific area of computer science and information technology research.
-
D.
SIGKDD
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.
-
E.
ACM Computing Surveys
ACM Computing Surveys is a leading peer-reviewed journal that publishes comprehensive, in-depth survey articles covering major areas of computer science and computing research.
- 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.