Triple
T8583307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Merit Cross (Austria-Hungary) |
E203238
|
entity |
| Predicate | swordsFeature |
P82966
|
FINISHED |
| Object | crossed swords through the center of the cross |
—
|
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: crossed swords through the center of the cross | Statement: [Military Merit Cross (Austria-Hungary), swordsFeature, crossed swords through the center of the cross]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: swordsFeature Context triple: [Military Merit Cross (Austria-Hungary), swordsFeature, crossed swords through the center of the cross]
-
A.
weaponFeature
Indicates that one entity is a characteristic, attribute, or functional aspect of a weapon.
-
B.
weaponForgedFor
Indicates that a weapon was specifically created or crafted for a particular entity, purpose, or context.
-
C.
greaterArmsFeature
Indicates that one entity possesses a more prominent or advanced arm-related feature than another entity.
-
D.
supportsWeapon
Indicates that one entity is capable of accommodating, using, or being compatible with a specified weapon.
-
E.
weaponForged
Indicates that one entity has been created or shaped as a weapon by another entity through a forging process.
- 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_69ca8329bb7c8190a63c643730839103 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbeb1d0edc8190b4495935275252f3 |
completed | March 31, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69cbd11b13108190b07f8f161425a585 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:22 p.m.