Triple
T16350345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuto Besak Fortress |
E397045
|
entity |
| Predicate | replaces |
P101
|
FINISHED |
| Object |
Kuto Lamo
Kuto Lamo was an earlier fortification or palace complex in Palembang, Indonesia, that historically preceded and was eventually superseded by the Kuto Besak Fortress.
|
E1209142
|
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: Kuto Lamo | Statement: [Kuto Besak Fortress, replaces, Kuto Lamo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuto Lamo Context triple: [Kuto Besak Fortress, replaces, Kuto Lamo]
-
A.
Kalaong
Kalaong is a barangay (village-level administrative division) of the municipality of Maitum in the province of Sarangani, Philippines.
-
B.
Jailolo
Jailolo is a historic coastal town and former sultanate on the island of Halmahera in Indonesia’s North Maluku province.
-
C.
Kalabahi
Kalabahi is the main town and administrative center on Alor Island in Indonesia’s East Nusa Tenggara province.
-
D.
Balungao
Balungao is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its hilly terrain and hot and cold springs.
-
E.
Kutoarjo
Kutoarjo is a town in Central Java, Indonesia, known as a regional transport hub and local commercial 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: Kuto Lamo Triple: [Kuto Besak Fortress, replaces, Kuto Lamo]
Generated description
Kuto Lamo was an earlier fortification or palace complex in Palembang, Indonesia, that historically preceded and was eventually superseded by the Kuto Besak Fortress.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kuto Lamo Target entity description: Kuto Lamo was an earlier fortification or palace complex in Palembang, Indonesia, that historically preceded and was eventually superseded by the Kuto Besak Fortress.
-
A.
Kalaong
Kalaong is a barangay (village-level administrative division) of the municipality of Maitum in the province of Sarangani, Philippines.
-
B.
Jailolo
Jailolo is a historic coastal town and former sultanate on the island of Halmahera in Indonesia’s North Maluku province.
-
C.
Kalabahi
Kalabahi is the main town and administrative center on Alor Island in Indonesia’s East Nusa Tenggara province.
-
D.
Balungao
Balungao is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its hilly terrain and hot and cold springs.
-
E.
Kutoarjo
Kutoarjo is a town in Central Java, Indonesia, known as a regional transport hub and local commercial 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_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.