Triple
T20692081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kota Gede |
E508575
|
entity |
| Predicate | craftSpecialization |
P98026
|
FINISHED |
| Object | metalworking |
—
|
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: metalworking | Statement: [Kota Gede, craftSpecialization, metalworking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: craftSpecialization Context triple: [Kota Gede, craftSpecialization, metalworking]
-
A.
craftSpecialty
chosen
Indicates that an entity has a particular area of specialized skill or focus within a craft or artisanal practice.
-
B.
creatorSpecialization
Indicates the specific field, discipline, or area of expertise in which a creator primarily works or is specialized.
-
C.
weaponProficiency
Indicates that an entity has the skill or qualification to effectively use a specified weapon.
-
D.
spellSpecialty
Indicates that an entity’s area of expertise or focus is a particular type or category of spell.
-
E.
skillType
Indicates the specific category or kind of skill that characterizes or classifies an associated skill-related entity or action.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10eaccc819085320fffbb0aeceb |
completed | April 21, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c044d1108190b2b5d25de23f6401 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:09 p.m.