Triple
T10330328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TEI |
E242855
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | TEI header |
E242855
|
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: TEI header | Statement: [TEI, hasComponent, TEI header]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TEI header Context triple: [TEI, hasComponent, TEI header]
-
A.
TEI
chosen
TEI (Text Encoding Initiative) is a widely used standard for encoding and representing texts in digital form, especially in the humanities, using XML-based guidelines.
-
B.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
-
C.
JATS
JATS (Journal Article Tag Suite) is an XML-based standard for tagging and exchanging scholarly journal content, widely used for structuring and archiving scientific articles.
-
D.
Dublin Core
Dublin Core is a widely used standard for describing digital resources through a simple, generic set of metadata elements to support discovery and interoperability across systems.
-
E.
IPTC NewsML-G2
IPTC NewsML-G2 is an XML-based standard for structuring, exchanging, and managing news and media content across digital systems and platforms.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71dbc7df48190b8a11a92f946fd30 |
completed | April 9, 2026, 3:32 a.m. |
Created at: April 6, 2026, 11:52 a.m.