Triple
T19731316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dronacharya |
E473859
|
entity |
| Predicate | weaponSpecialization |
P131403
|
FINISHED |
| Object | bow and arrow |
—
|
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: bow and arrow | Statement: [Dronacharya, weaponSpecialization, bow and arrow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weaponSpecialization Context triple: [Dronacharya, weaponSpecialization, bow and arrow]
-
A.
weaponProficiency
chosen
Indicates that an entity has the skill or qualification to effectively use a specified weapon.
-
B.
weaponDiscipline
Indicates that an entity practices, adheres to, or is governed by a particular system, style, or code of weapon use or combat training.
-
C.
specialWeapon
Indicates that an entity is a weapon with unique, enhanced, or otherwise exceptional properties compared to standard weapons.
-
D.
craftSpecialty
Indicates that an entity has a particular area of specialized skill or focus within a craft or artisanal practice.
-
E.
unitSpecialization
Indicates that one unit is a specialized or more specific version of another unit within a hierarchical or categorical relationship.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649fd18148190a6e85b2be0069dde |
completed | April 20, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.