Triple
T18881534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raumanga |
E461838
|
entity |
| Predicate | hasNearbySuburb |
P41355
|
FINISHED |
| Object |
Otaika
Otaika is a semi-rural suburb on the southern outskirts of Whangārei in New Zealand’s Northland Region.
|
E1347035
|
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: Otaika | Statement: [Raumanga, hasNearbySuburb, Otaika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Otaika Context triple: [Raumanga, hasNearbySuburb, Otaika]
-
A.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
-
B.
Ota
Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
-
C.
Ota
Ōta is a major industrial city in Japan’s northern Kantō region, known especially for its automotive manufacturing, including the headquarters and main plants of Subaru.
-
D.
Ota
Ota is a civil parish in Portugal, known for its location within the municipality of Alenquer in the Lisbon District.
-
E.
Ota
Ota is a small commune in the Corse-du-Sud department of Corsica, France, known for its dramatic coastal and mountain scenery and proximity to the UNESCO-listed Gulf of Porto.
- 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: Otaika Triple: [Raumanga, hasNearbySuburb, Otaika]
Generated description
Otaika is a semi-rural suburb on the southern outskirts of Whangārei in New Zealand’s Northland Region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Otaika Target entity description: Otaika is a semi-rural suburb on the southern outskirts of Whangārei in New Zealand’s Northland Region.
-
A.
Ota
Ota is a historically significant Awori town in southwestern Nigeria that has grown into a major industrial and educational hub.
-
B.
Ota
Ōta is a large ward in southern Tokyo, Japan, known for Haneda Airport, residential neighborhoods, and a mix of industrial and commercial areas.
-
C.
Ota
Ōta is a major industrial city in Japan’s northern Kantō region, known especially for its automotive manufacturing, including the headquarters and main plants of Subaru.
-
D.
Ota
Ota is a civil parish in Portugal, known for its location within the municipality of Alenquer in the Lisbon District.
-
E.
Ota
Ota is a small commune in the Corse-du-Sud department of Corsica, France, known for its dramatic coastal and mountain scenery and proximity to the UNESCO-listed Gulf of Porto.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d2028481908af2b1560312e26c |
completed | April 20, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0575c4f044819086125edb8d0f07ca |
completed | May 14, 2026, 7:12 a.m. |
| NEDg | Description generation | batch_6a057954c5b88190937627ae912260d2 |
completed | May 14, 2026, 7:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0579b6fc3c8190979029570f06a546 |
completed | May 14, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:57 a.m.