Triple
T239420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IANA time zone database |
E4894
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | PHP |
E22482
|
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: PHP | Statement: [IANA time zone database, usedBy, PHP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PHP Context triple: [IANA time zone database, usedBy, PHP]
-
A.
PHP
PHP is the three-letter ISO 4217 currency code for the Philippine peso, the official monetary unit of the Philippines.
-
B.
PHP
chosen
PHP is a widely used open-source server-side scripting language especially suited for web development and powering dynamic websites and applications.
-
C.
JavaScript
JavaScript is a high-level, dynamic programming language primarily used to create interactive and dynamic content on web pages.
-
D.
Python
Python is a high-level, versatile programming language widely used for data analysis, machine learning, web development, and automation.
-
E.
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.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ceaecdc81909e9ff49cb6a4e02a |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3695ec8cc8190a070462cd0022f6a |
completed | Feb. 28, 2026, 10:17 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.