Triple
T1384873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sumba |
E29821
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Tambolaka
Tambolaka is a town on the Indonesian island of Sumba that serves as an important local hub with an airport and access point for exploring the island.
|
E169903
|
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: Tambolaka | Statement: [Sumba, hasTown, Tambolaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tambolaka Context triple: [Sumba, hasTown, Tambolaka]
-
A.
Tongaat
Tongaat is a town in KwaZulu-Natal, South Africa, known for its significant Indian community and sugar industry.
-
B.
Tontola
Tontola is a small locality or hamlet that forms part of the municipality of Predappio in the Emilia-Romagna region of Italy.
-
C.
Ronga
Ronga is a Bantu language spoken primarily in southern Mozambique, known for contributing vocabulary and structural features to African varieties of Portuguese.
-
D.
Lokoja
Lokoja is a city in central Nigeria located at the strategic confluence of the Niger and Benue rivers and serves as the capital of Kogi State.
-
E.
Ketambe
Ketambe is a remote village in Aceh, Indonesia, known as a key access point for jungle trekking and wildlife viewing in the Gunung Leuser ecosystem, especially for observing wild orangutans.
- 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: Tambolaka Triple: [Sumba, hasTown, Tambolaka]
Generated description
Tambolaka is a town on the Indonesian island of Sumba that serves as an important local hub with an airport and access point for exploring the island.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tambolaka Target entity description: Tambolaka is a town on the Indonesian island of Sumba that serves as an important local hub with an airport and access point for exploring the island.
-
A.
Tongaat
Tongaat is a town in KwaZulu-Natal, South Africa, known for its significant Indian community and sugar industry.
-
B.
Tontola
Tontola is a small locality or hamlet that forms part of the municipality of Predappio in the Emilia-Romagna region of Italy.
-
C.
Ronga
Ronga is a Bantu language spoken primarily in southern Mozambique, known for contributing vocabulary and structural features to African varieties of Portuguese.
-
D.
Lokoja
Lokoja is a city in central Nigeria located at the strategic confluence of the Niger and Benue rivers and serves as the capital of Kogi State.
-
E.
Ketambe
Ketambe is a remote village in Aceh, Indonesia, known as a key access point for jungle trekking and wildlife viewing in the Gunung Leuser ecosystem, especially for observing wild orangutans.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c33896548190b44f70c9aaaed9b6 |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c97ba748190a227457bcb87a733 |
completed | March 8, 2026, 6:52 a.m. |
| NEDg | Description generation | batch_69ad1d1eccfc81909bdf4df141d1987f |
completed | March 8, 2026, 6:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad1d8cea008190be2557f6804a261f |
completed | March 8, 2026, 6:56 a.m. |
Created at: March 1, 2026, 7:59 p.m.