Triple
T21990048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAX |
E543058
|
entity |
| Predicate | alternativeTo |
P5887
|
FINISHED |
| Object | DOM |
—
|
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: DOM | Statement: [SAX, alternativeTo, DOM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DOM Context triple: [SAX, alternativeTo, DOM]
-
A.
DOM
chosen
The Document Object Model (DOM) is a platform- and language-neutral interface that represents structured documents like HTML and XML as a tree of objects, enabling programs and scripts to dynamically access and update their content and structure.
-
B.
DOM
DOM is the three-letter ISO 3166-1 alpha-3 country code assigned to the Dominican Republic.
-
C.
DHTML
DHTML (Dynamic HTML) is a web development technique that combines HTML, CSS, and JavaScript to create interactive and animated web pages that update content dynamically without reloading.
-
D.
CSS Object Model (CSSOM)
The CSS Object Model (CSSOM) is a programming interface that represents CSS styles as a structured tree, enabling scripts to read and manipulate the styling and layout of web documents dynamically.
-
E.
DOM Level 2
DOM Level 2 is a W3C specification that extends the Document Object Model with standardized interfaces for events, traversal, ranges, and improved document manipulation in web browsers.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270cb67c81909a3aa2dc61c1894f |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.