Triple
T2102785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dulce et Decorum Est |
E37127
|
entity |
| Predicate | fullLatinTaglineMeaning |
P35842
|
FINISHED |
| Object | It is sweet and fitting to die for one’s country |
—
|
LITERAL 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: It is sweet and fitting to die for one’s country | Statement: [Dulce et Decorum Est, fullLatinTaglineMeaning, It is sweet and fitting to die for one’s country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fullLatinTaglineMeaning Context triple: [Dulce et Decorum Est, fullLatinTaglineMeaning, It is sweet and fitting to die for one’s country]
-
A.
hasLatinTitle
Indicates that an entity possesses a title or name expressed in Latin.
-
B.
codeNameMeaning
Indicates that one entity is the meaning, interpretation, or significance associated with another entity’s code name.
-
C.
sourceLanguageMeaning
Indicates that one entity expresses the meaning or sense of another entity in a particular source language.
-
D.
meaningOfPhrase
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
E.
titleMeaning
Indicates that one entity expresses or explains the meaning, significance, or interpretation of another entity’s title.
- F. None of above. chosen
Provenance (4 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabe1e9081908ea66c5406e2f1d9 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb9ce3ff08190a9501f8bb821c01c |
completed | March 7, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:43 p.m.