Triple
T4186134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airlangga |
E88315
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | Kediri |
E181796
|
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: Kediri | Statement: [Airlangga, successor, Kediri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kediri Context triple: [Airlangga, successor, Kediri]
-
A.
Kediri
chosen
Kediri is a historic city in Indonesia known for its role as a former Javanese kingdom center and as an important economic hub in modern East Java.
-
B.
Pasuruan
Pasuruan is a city in East Java, Indonesia, known as a gateway to the popular Mount Bromo volcanic tourism area.
-
C.
Cirebon
Cirebon is a coastal city in West Java, Indonesia, known as a cultural crossroads blending Sundanese and Javanese influences and serving as a significant regional trading and urban center.
-
D.
Malang
Malang is a major city in East Java, Indonesia, known for its cool climate, colonial-era architecture, and proximity to popular mountain and volcanic tourist destinations.
-
E.
Jember
Jember is a regency and major urban center in eastern Java, Indonesia, known for its agricultural economy and cultural festivals such as the Jember Fashion Carnaval.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af032490888190bbfa422003caca99 |
completed | March 9, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5db77e7d88190a7ba250972e133fa |
completed | March 14, 2026, 10:04 p.m. |
Created at: March 9, 2026, 3:45 p.m.