Triple
T1521213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cipinang Prison |
E32231
|
entity |
| Predicate | locatedInNeighborhood |
P40
|
FINISHED |
| Object |
Cipinang
Cipinang is a neighborhood in East Jakarta, Indonesia, known for housing one of the country’s main prisons and various urban residential and commercial areas.
|
E187323
|
NE FINISHED |
How this triple was built (4 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: Cipinang | Statement: [Cipinang Prison, locatedInNeighborhood, Cipinang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cipinang Context triple: [Cipinang Prison, locatedInNeighborhood, Cipinang]
-
A.
Tanjung Priok
Tanjung Priok is Indonesia’s busiest and largest seaport, serving as the main maritime gateway to Jakarta and the island of Java.
-
B.
Cimahi
Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training center.
-
C.
Sunda Kelapa
Sunda Kelapa is the historic old port area of Jakarta, Indonesia, known as a key trading hub in the region since precolonial times.
-
D.
Cilegon
Cilegon is an industrial port city in western Java, Indonesia, known for its steel industry and strategic location near the Sunda Strait.
-
E.
Bogor
Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cipinang Triple: [Cipinang Prison, locatedInNeighborhood, Cipinang]
Generated description
Cipinang is a neighborhood in East Jakarta, Indonesia, known for housing one of the country’s main prisons and various urban residential and commercial areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cipinang Target entity description: Cipinang is a neighborhood in East Jakarta, Indonesia, known for housing one of the country’s main prisons and various urban residential and commercial areas.
-
A.
Tanjung Priok
Tanjung Priok is Indonesia’s busiest and largest seaport, serving as the main maritime gateway to Jakarta and the island of Java.
-
B.
Cimahi
Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training center.
-
C.
Sunda Kelapa
Sunda Kelapa is the historic old port area of Jakarta, Indonesia, known as a key trading hub in the region since precolonial times.
-
D.
Cilegon
Cilegon is an industrial port city in western Java, Indonesia, known for its steel industry and strategic location near the Sunda Strait.
-
E.
Bogor
Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
- F. None of above. chosen
Provenance (5 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907f071848190a5fb8fa1b97ef4de |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad680440dc8190ad28ec47c5a35d28 |
completed | March 8, 2026, 12:13 p.m. |
| NEDg | Description generation | batch_69ad68d482948190852098c5e80ad67b |
completed | March 8, 2026, 12:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad693e60048190bb2179a958a72452 |
completed | March 8, 2026, 12:19 p.m. |
Created at: March 4, 2026, 7:26 p.m.