Triple
T22617898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Ghana |
E558195
|
entity |
| Predicate | linguistStaffAndSwordRepresent |
P148951
|
FINISHED |
| Object | traditional authority |
—
|
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: traditional authority | Statement: [coat of arms of Ghana, linguistStaffAndSwordRepresent, traditional authority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguistStaffAndSwordRepresent Context triple: [coat of arms of Ghana, linguistStaffAndSwordRepresent, traditional authority]
-
A.
swordsRepresent
Indicates that swords serve as symbols or stand-ins representing a particular idea, group, concept, or entity.
-
B.
swornSword
Indicates a formal oath of loyalty in which one entity pledges to serve and protect another as their sworn sword.
-
C.
swordsFeature
Indicates that something includes or prominently presents swords as a notable element or characteristic.
-
D.
hasLinguist
Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
-
E.
symbolicWeapon
Indicates a relationship where something functions as a symbolic or emblematic weapon for an entity, representing power, threat, or conflict rather than serving as a literal physical armament.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f167ef7a148190870334af9c8b79a4 |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:59 p.m.