Triple
T21171849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pekalongan Batik Museum |
E521709
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Pekalongan |
—
|
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: Pekalongan | Statement: [Pekalongan Batik Museum, locatedIn, Pekalongan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pekalongan Context triple: [Pekalongan Batik Museum, locatedIn, Pekalongan]
-
A.
Pekalongan
chosen
Pekalongan is an Indonesian coastal city on the island of Java renowned as a major center of batik production and textile arts.
-
B.
Tegal
Tegal is a coastal city in Central Java, Indonesia, known as a regional transport hub and trading center on the north coast railway line.
-
C.
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.
-
D.
Purworejo
Purworejo is a regency in Central Java, Indonesia, known for its agricultural landscape and proximity to the southern coast of Java.
-
E.
Blora
Blora is a regency-level town in Indonesia known for its teak forests and cultural heritage, located in the eastern part of Central Java.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7271351f08190b609a6c280c9a02a |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.