Triple
T17276713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Java |
E419410
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tegal |
—
|
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: Tegal | Statement: [Central Java, contains, Tegal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tegal Context triple: [Central Java, contains, Tegal]
-
A.
Tegal
chosen
Tegal is a coastal city in Central Java, Indonesia, known as a regional transport hub and trading center on the north coast railway line.
-
B.
Semarang
Semarang is a major coastal city on the north coast of Java in Indonesia, known historically as an important colonial trading hub and now as a significant commercial and industrial center.
-
C.
Pekalongan
Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
-
D.
Tegal Regency
Tegal Regency is an administrative region in Central Java, Indonesia, known for its agricultural economy, coastal areas along the Java Sea, and cultural ties to the city of Tegal.
-
E.
Purwokerto
Purwokerto is a major town in Central Java, Indonesia, known as a regional economic and educational center and a gateway to nearby highland tourist destinations.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e43326ec908190934a858c30cca880 |
completed | April 19, 2026, 1:43 a.m. |
Created at: April 10, 2026, 5:40 a.m.