Triple
T16350281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sriwijaya University |
E397044
|
entity |
| Predicate | hasCampusIn |
P4623
|
FINISHED |
| Object |
Indralaya
Indralaya is a town in South Sumatra, Indonesia, known as an educational hub due to hosting the main campus of Sriwijaya University.
|
E1209130
|
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: Indralaya | Statement: [Sriwijaya University, hasCampusIn, Indralaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Indralaya Context triple: [Sriwijaya University, hasCampusIn, Indralaya]
-
A.
Balambat
Balambat is a town and administrative area in Pakistan’s Khyber Pakhtunkhwa province, situated within the mountainous region of Lower Dir.
-
B.
Latri Kunda
Latri Kunda is a neighborhood within the urban area of Serekunda in The Gambia, known for its busy streets and local commerce.
-
C.
Indrapura
Indrapura was a prominent historical capital city of the Champa kingdom in what is now central Vietnam.
-
D.
Wetar-Dai
Wetar-Dai is an Austronesian language variety spoken on Wetar Island in Indonesia, closely related to other Central Malayo-Polynesian languages.
-
E.
Mirani
Mirani is a small rural town and locality in Queensland, Australia, known for its sugarcane farming and proximity to the Pioneer Valley.
- 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: Indralaya Triple: [Sriwijaya University, hasCampusIn, Indralaya]
Generated description
Indralaya is a town in South Sumatra, Indonesia, known as an educational hub due to hosting the main campus of Sriwijaya University.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Indralaya Target entity description: Indralaya is a town in South Sumatra, Indonesia, known as an educational hub due to hosting the main campus of Sriwijaya University.
-
A.
Balambat
Balambat is a town and administrative area in Pakistan’s Khyber Pakhtunkhwa province, situated within the mountainous region of Lower Dir.
-
B.
Latri Kunda
Latri Kunda is a neighborhood within the urban area of Serekunda in The Gambia, known for its busy streets and local commerce.
-
C.
Indrapura
Indrapura was a prominent historical capital city of the Champa kingdom in what is now central Vietnam.
-
D.
Wetar-Dai
Wetar-Dai is an Austronesian language variety spoken on Wetar Island in Indonesia, closely related to other Central Malayo-Polynesian languages.
-
E.
Mirani
Mirani is a small rural town and locality in Queensland, Australia, known for its sugarcane farming and proximity to the Pioneer Valley.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2da120ec081909bbf32bd128b2e01 |
completed | April 18, 2026, 1:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002db40e0481908d919f2285e48a23 |
completed | May 10, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_6a003082f0008190aeae2fbbfc3a8acf |
completed | May 10, 2026, 7:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00312a4fc48190b6bd6ad9db71bb4d |
completed | May 10, 2026, 7:18 a.m. |
Created at: April 10, 2026, 5:07 a.m.