Triple
T20460090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TR-85M1 Bizonul |
E501900
|
entity |
| Predicate | hasSideSkirts |
P116516
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [TR-85M1 Bizonul, hasSideSkirts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSideSkirts Context triple: [TR-85M1 Bizonul, hasSideSkirts, yes]
-
A.
hasSkirtType
chosen
Indicates that an entity is associated with or characterized by a specific type or style of skirt.
-
B.
hasSideArch
Indicates that one entity possesses or features a secondary or lateral arch structure in relation to another entity.
-
C.
hasRacingSide
Indicates that an entity possesses or is associated with a side or aspect specifically dedicated to racing.
-
D.
hasFrill
Indicates that one entity possesses or is characterized by a frill as a distinguishing feature or component.
-
E.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
- F. None of above.
Provenance (3 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a549a48190a1bcd7a6b0f71a11 |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.