Triple
T400510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C |
E9269
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Perl |
E17647
|
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: Perl | Statement: [C, influenced, Perl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perl Context triple: [C, influenced, Perl]
-
A.
PyPy
PyPy is a high-performance alternative Python interpreter featuring a Just-In-Time (JIT) compiler designed to significantly speed up the execution of Python programs.
-
B.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
C.
Ruby
chosen
Ruby is a dynamic, object-oriented programming language known for its elegant syntax and its use in the Ruby on Rails web framework.
-
D.
PHP
PHP is the three-letter ISO 4217 currency code for the Philippine peso, the official monetary unit of the Philippines.
-
E.
PHP
PHP is a widely used open-source server-side scripting language especially suited for web development and powering dynamic websites and applications.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4103f9f588190aabdf7f5d6422d09 |
completed | March 1, 2026, 10:09 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.