Triple
T22933540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tukang Besi North |
E569510
|
entity |
| Predicate | isVarietyOf |
P2074
|
FINISHED |
| Object | Tukang Besi |
—
|
NE NERFINISHED |
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: Tukang Besi | Statement: [Tukang Besi North, isVarietyOf, Tukang Besi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tukang Besi Context triple: [Tukang Besi North, isVarietyOf, Tukang Besi]
-
A.
Tukang Besi North
chosen
Tukang Besi North is a regional variety of the Tukang Besi language spoken in parts of Southeast Sulawesi, Indonesia.
-
B.
Oceláři
Oceláři is the nickname of HC Oceláři Třinec, a prominent professional ice hockey club based in Třinec, Czech Republic.
-
C.
Ferreiros
Ferreiros is a municipality in the state of Pernambuco, Brazil, that forms part of the Recife metropolitan area.
-
D.
The Blacksmiths
"The Blacksmiths" is a 1932 British documentary film by George Dyson that portrays the traditional craft and daily work of blacksmiths.
-
E.
The Blacksmith
The Blacksmith is a painting by Dutch Golden Age artist Abraham Bloemaert depicting a craftsman at work in a dramatic, chiaroscuro-lit forge.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458f7d008190901dccbaebeaba24 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181337ff881909d90cf3f5bae7516 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:44 p.m.