Triple
T8447361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diana Prince |
E199708
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Themysciran |
E733910
|
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: Themysciran | Statement: [Diana Prince, language, Themysciran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Themysciran Context triple: [Diana Prince, language, Themysciran]
-
A.
Themysciran
chosen
Themysciran refers to the fictional Amazonian people and culture from the hidden island of Themyscira in DC Comics, best known as the homeland of Wonder Woman.
-
B.
Terra Cimmeria
Terra Cimmeria is a heavily cratered, ancient highland region in Mars’s southern hemisphere, notable for its rugged terrain and geological history.
-
C.
Cyndia
Cyndia is an alternative given name or spelling derived from the name Cynthia.
-
D.
Kydonia
Kydonia was an important ancient city on the northwest coast of Crete, known as a significant political and commercial center in Bronze Age Aegean history.
-
E.
Angria
Angria was a historical region that formed one of the main parts of the medieval Duchy of Saxony in what is now northern Germany.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44480ec8190b32443a53cd4f943 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce39b528f08190a0627cb17a0ffef9 |
completed | April 2, 2026, 9:41 a.m. |
Created at: March 30, 2026, 6:09 p.m.