Triple
T16831754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Guatemala |
E409166
|
entity |
| Predicate | riflesRepresent |
P125019
|
FINISHED |
| Object | willingness to defend freedom |
—
|
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: willingness to defend freedom | Statement: [Coat of arms of Guatemala, riflesRepresent, willingness to defend freedom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riflesRepresent Context triple: [Coat of arms of Guatemala, riflesRepresent, willingness to defend freedom]
-
A.
isServiceRifleOf
Indicates that one entity is the designated service rifle used by another entity, typically a military or armed force.
-
B.
numberOfGuns
Indicates the quantity of guns associated with a given entity or situation.
-
C.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
D.
rifleConference
Indicates a relationship where an entity organizes, participates in, or is otherwise involved with a conference focused on rifles or rifle-related topics.
-
E.
Berdan No.1 rifle
Indicates that an entity is a Berdan No.1 rifle, i.e., it has the identity or classification of that specific rifle model.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b317af8c8190a09cb6d60d28e342 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.