Triple
T22438574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Division of Training and Development |
E554692
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | DTD |
—
|
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: DTD | Statement: [Division of Training and Development, abbreviation, DTD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DTD Context triple: [Division of Training and Development, abbreviation, DTD]
-
A.
DTD
DTD (Document Type Definition) is an XML schema language used to define the legal structure, elements, and attributes of an XML document.
-
B.
DTD
chosen
DTD is the abbreviated name for the Division of Training and Development, an organizational unit focused on designing and delivering training and professional development programs.
-
C.
DTML
DTML (Document Template Markup Language) is a server-side scripting and templating language used in the Zope web application framework to generate dynamic web content.
-
D.
SGML
SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
-
E.
DITA
DITA (Darwin Information Typing Architecture) is an XML-based standard for authoring, structuring, and publishing modular technical documentation.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae01bd08190aee5141f4c0848bc |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.