Triple
T6033551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ECMA-404 |
E134363
|
entity |
| Predicate | definesSyntaxFor |
P38052
|
FINISHED |
| Object | JSON number |
E39004
|
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: JSON number | Statement: [ECMA-404, definesSyntaxFor, JSON number]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JSON number Context triple: [ECMA-404, definesSyntaxFor, JSON number]
-
A.
JSON
chosen
JSON (JavaScript Object Notation) is a lightweight, text-based data interchange format widely used for transmitting structured data in web APIs and configuration files.
-
B.
JSON5
JSON5 is an extension of the JSON data format that adds more human-friendly features like comments, trailing commas, and unquoted object keys while remaining largely compatible with standard JSON.
-
C.
Numbers
Numbers is Apple's spreadsheet application for macOS and iOS, used to create, analyze, and visualize data in tables and charts.
-
D.
Numbers
Numbers is the fourth book of the Hebrew Bible and the Christian Old Testament, recounting the Israelites’ wilderness wanderings and organizing laws and censuses.
-
E.
NUM
NUM is a common abbreviation for the National University of Mongolia, the country’s oldest and largest public university and a leading center of higher education and research in Mongolia.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b220608190b156be95632cf3b3 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113855ad08190b9ff826a2f39c356 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:08 p.m.