Triple
T13864779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinjai Regency |
E333294
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object |
Sinjai
Sinjai is a town in South Sulawesi, Indonesia, known as an administrative and commercial center for the surrounding Sinjai Regency.
|
E333294
|
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: Sinjai | Statement: [Sinjai Regency, seat, Sinjai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinjai Context triple: [Sinjai Regency, seat, Sinjai]
-
A.
Sinjai Regency
Sinjai Regency is an administrative region in Indonesia known for its coastal landscapes, agricultural activities, and cultural diversity within the province of South Sulawesi.
-
B.
Payakumbuh
Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
-
C.
Sidrap Regency
Sidrap Regency is an administrative region in South Sulawesi, Indonesia, known for its agricultural activities and location in the island’s central area.
-
D.
Tondano
Tondano is a town in North Sulawesi, Indonesia, known as an administrative and cultural center of the Minahasa region near Lake Tondano.
-
E.
Makasar
Makasar is a district in East Jakarta, Indonesia, known as a primarily residential and urban area within the capital’s eastern region.
- 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: Sinjai Triple: [Sinjai Regency, seat, Sinjai]
Generated description
Sinjai is a town in South Sulawesi, Indonesia, known as an administrative and commercial center for the surrounding Sinjai Regency.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sinjai Target entity description: Sinjai is a town in South Sulawesi, Indonesia, known as an administrative and commercial center for the surrounding Sinjai Regency.
-
A.
Sinjai Regency
chosen
Sinjai Regency is an administrative region in Indonesia known for its coastal landscapes, agricultural activities, and cultural diversity within the province of South Sulawesi.
-
B.
Payakumbuh
Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
-
C.
Sidrap Regency
Sidrap Regency is an administrative region in South Sulawesi, Indonesia, known for its agricultural activities and location in the island’s central area.
-
D.
Tondano
Tondano is a town in North Sulawesi, Indonesia, known as an administrative and cultural center of the Minahasa region near Lake Tondano.
-
E.
Makasar
Makasar is a district in East Jakarta, Indonesia, known as a primarily residential and urban area within the capital’s eastern region.
- F. None of above.
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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c30d9c81908217d41a3b4aaf85 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd27f8f388819096c7c33b90f9ac4c |
completed | May 8, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69fd2aeea5808190bf350b25f520e6d4 |
completed | May 8, 2026, 12:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2b57474881909f780cf51c2e06a3 |
completed | May 8, 2026, 12:16 a.m. |
Created at: April 9, 2026, 10:14 p.m.