Triple
T18770596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ECMA standard |
E459007
|
entity |
| Predicate | hasExample |
P1259
|
FINISHED |
| Object | ECMA-262 |
—
|
NE NERFINISHED |
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: ECMA-262 | Statement: [ECMA standard, hasExample, ECMA-262]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ECMA-262 Context triple: [ECMA standard, hasExample, ECMA-262]
-
A.
ECMAScript
chosen
ECMAScript is the official scripting language specification that defines the core features and behavior implemented by JavaScript and related languages.
-
B.
ECMA standard
An ECMA standard is a technical specification published by Ecma International that defines interoperable formats, languages, or interfaces for information and communication systems.
-
C.
ECMA-372
ECMA-372 is the ECMA standard that defines the C++/CLI language specification for managed extensions of C++ targeting the .NET runtime.
-
D.
ECMA-340
ECMA-340 is an international standard that specifies the Near Field Communication (NFC) interface and protocol for short-range wireless communication between electronic devices.
-
E.
ECMA-367
ECMA-367 is the official international standard that defines the syntax and semantics of the Eiffel programming language.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59335a01881908731371be1e27a6b |
completed | April 20, 2026, 2:45 a.m. |
Created at: April 10, 2026, 11:52 a.m.