Triple
T7666273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Meyers |
E173630
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | Effective STL |
E173632
|
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: Effective STL | Statement: [Scott Meyers, knownFor, Effective STL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Effective STL Context triple: [Scott Meyers, knownFor, Effective STL]
-
A.
Effective STL
chosen
Effective STL is a programming book by Scott Meyers that provides practical guidelines and best practices for using the C++ Standard Template Library effectively and efficiently.
-
B.
STL
STL is a common abbreviation and nickname for the city of St. Louis, Missouri.
-
C.
Exceptional C++ Style
Exceptional C++ Style is a programming book by Herb Sutter that focuses on advanced C++ design, idioms, and best practices for writing high-quality, modern C++ code.
-
D.
Effective C++
Effective C++ is a widely respected programming book by Scott Meyers that presents practical guidelines and best practices for writing robust, efficient C++ code.
-
E.
STLAM
STLAM is the stock ticker symbol for Stellantis, a multinational automotive manufacturer formed from the merger of Fiat Chrysler Automobiles and PSA Group.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701c1383c8190ab5bf803bd6211a9 |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b1fdccc8190a69b4745dc3b2347 |
completed | March 29, 2026, 3:23 a.m. |
Created at: March 27, 2026, 4 p.m.