Triple
T8340259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Jakarta |
E195890
|
entity |
| Predicate | hasShoppingArea |
P4285
|
FINISHED |
| Object |
Kemang
Kemang is a trendy neighborhood in South Jakarta known for its vibrant nightlife, cafes, boutiques, and expatriate-friendly atmosphere.
|
E728523
|
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: Kemang | Statement: [South Jakarta, hasShoppingArea, Kemang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kemang Context triple: [South Jakarta, hasShoppingArea, Kemang]
-
A.
Kemang
Kemang is a district-level area located within Bogor Regency in West Java, Indonesia.
-
B.
Mangseng
Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
-
C.
Pakualaman
Pakualaman is a small hereditary Javanese princely state and court within Yogyakarta, established in the 19th century as a minor parallel to the main sultanate.
-
D.
Pakpak Keppas
Pakpak Keppas is a regional dialect of the Pakpak Dairi language spoken by the Pakpak ethnic community in parts of North Sumatra, Indonesia.
-
E.
Kemusuk
Kemusuk is a small village in Yogyakarta, Indonesia, best known as the birthplace of former Indonesian president Suharto.
- 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: Kemang Triple: [South Jakarta, hasShoppingArea, Kemang]
Generated description
Kemang is a trendy neighborhood in South Jakarta known for its vibrant nightlife, cafes, boutiques, and expatriate-friendly atmosphere.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kemang Target entity description: Kemang is a trendy neighborhood in South Jakarta known for its vibrant nightlife, cafes, boutiques, and expatriate-friendly atmosphere.
-
A.
Kemang
Kemang is a district-level area located within Bogor Regency in West Java, Indonesia.
-
B.
Mangseng
Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
-
C.
Pakualaman
Pakualaman is a small hereditary Javanese princely state and court within Yogyakarta, established in the 19th century as a minor parallel to the main sultanate.
-
D.
Pakpak Keppas
Pakpak Keppas is a regional dialect of the Pakpak Dairi language spoken by the Pakpak ethnic community in parts of North Sumatra, Indonesia.
-
E.
Kemusuk
Kemusuk is a small village in Yogyakarta, Indonesia, best known as the birthplace of former Indonesian president Suharto.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd7a3888190b54306ed862aded4 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc7237aa0819092b3679a318223ba |
completed | April 2, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69cdcc8596888190867bb0f298b6fac1 |
completed | April 2, 2026, 1:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdd14de9408190a5522fbdbef4d748 |
completed | April 2, 2026, 2:15 a.m. |
Created at: March 30, 2026, 5:57 p.m.