Triple
T9889633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banliang coin |
E181419
|
entity |
| Predicate | hasReverseFeature |
P91631
|
FINISHED |
| Object | usually blank reverse |
—
|
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: usually blank reverse | Statement: [Banliang coin, hasReverseFeature, usually blank reverse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReverseFeature Context triple: [Banliang coin, hasReverseFeature, usually blank reverse]
-
A.
hasReverse
Indicates that one entity serves as the inverse or opposite counterpart of another entity in a given relationship or operation.
-
B.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
C.
hasTwinFeature
Indicates that two entities share an identical or nearly identical feature, characteristic, or component, as if they are twins in that respect.
-
D.
featuresInversion
Indicates that one entity exhibits or incorporates an inversion of another entity, such as a reversed, mirrored, or otherwise inverted form or structure.
-
E.
isFeatureOf
Indicates that something functions as a characteristic, attribute, or component belonging to or describing another entity.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb47be2988190811a99dc56ae542a |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd36f112bc81908b473787e702de2f |
completed | April 1, 2026, 3:17 p.m. |
Created at: March 30, 2026, 8:39 p.m.