Triple
T8897003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sword of Mercy |
E211828
|
entity |
| Predicate | bladeCharacteristic |
P44775
|
FINISHED |
| Object | blunt tip |
—
|
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: blunt tip | Statement: [Sword of Mercy, bladeCharacteristic, blunt tip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bladeCharacteristic Context triple: [Sword of Mercy, bladeCharacteristic, blunt tip]
-
A.
bladeDetail
chosen
Indicates that there is specific descriptive information or characteristics associated with a blade.
-
B.
bladeType
Indicates the specific kind or category of blade associated with an object or entity.
-
C.
bladeEdge
Indicates that one entity is the cutting edge or sharpened boundary of a blade-related object in relation to another entity.
-
D.
tailCharacteristic
Indicates that an entity possesses a particular property, feature, or quality specifically related to its tail.
-
E.
equipmentCharacteristic
Indicates that a specific characteristic, property, or attribute is associated with a piece of equipment.
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6424a8c08190aef2aa2079dd85f1 |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2bfb38819083d5eb1af8ccf4d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:54 p.m.