Triple
T5233316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DPD |
E118158
|
entity |
| Predicate | meetsAt |
P373
|
FINISHED |
| Object | Senayan, Jakarta |
E505003
|
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: Senayan, Jakarta | Statement: [DPD, meetsAt, Senayan, Jakarta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senayan, Jakarta Context triple: [DPD, meetsAt, Senayan, Jakarta]
-
A.
Senayan, Jakarta
chosen
Senayan, Jakarta is a central district in Indonesia’s capital city known for its major government buildings, sports complex, and commercial centers.
-
B.
Jatinegara
Jatinegara is a district in East Jakarta, Indonesia, known as a densely populated urban area with significant transportation hubs and historical sites.
-
C.
Salemba, Central Jakarta, Indonesia
Salemba in Central Jakarta, Indonesia, is a prominent urban district known as an educational and institutional hub, notably hosting major campuses and government offices.
-
D.
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.
-
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.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0389048190b55b7c44fe657044 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe604a848190a3f6cc90185b3ca2 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:49 p.m.