Triple
T3060705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerbangkertosusila |
E60588
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Lamongan |
E203569
|
NE 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: Lamongan | Statement: [Gerbangkertosusila, namedAfter, Lamongan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lamongan Context triple: [Gerbangkertosusila, namedAfter, Lamongan]
-
A.
Lamongan
chosen
Lamongan is a regency and its capital town in the northern coastal region of East Java, Indonesia, known for its fishing industry and distinctive local cuisine.
-
B.
Jombang
Jombang is a regency-level town in Indonesia known as an important regional center in the province of East Java.
-
C.
Nganjuk
Nganjuk is a regency capital and regional urban center in the province of East Java, Indonesia.
-
D.
Gresik
Gresik is an industrial and port city in Indonesia known for its cement production and role as part of the Surabaya metropolitan area.
-
E.
Tulungagung
Tulungagung is a regency and urban center in southern East Java, Indonesia, known for its marble industry and coastal landscapes along the Indian Ocean.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9e9e1e248190b5ed5ebcdad1321e |
completed | March 8, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b595d57bcc8190b2a6e28437a32b93 |
completed | March 14, 2026, 5:07 p.m. |
Created at: March 8, 2026, 3:02 p.m.