Triple
T19029572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gisborne wine region |
E465698
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object |
Manutuke
Manutuke is a subregion of New Zealand’s Gisborne wine area, known for its viticulture and wine production.
|
E1354720
|
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: Manutuke | Statement: [Gisborne wine region, hasSubregion, Manutuke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manutuke Context triple: [Gisborne wine region, hasSubregion, Manutuke]
-
A.
Maskun
Maskun was an Indonesian politician associated with the nationalist movement and the Indonesian National Party.
-
B.
Mankessim
Mankessim is a major commercial and historical town in Ghana known as an important market center and traditional seat of the Fante people.
-
C.
Mansaka
Mansaka is an Austronesian language spoken by the indigenous Mansaka people of southeastern Mindanao in the Philippines.
-
D.
Tettamanzi
Tettamanzi is an Italian surname most notably associated with Cardinal Dionigi Tettamanzi, a prominent figure in the Roman Catholic Church.
-
E.
Mantena
Mantena is a Norwegian company that specializes in the maintenance and servicing of railway rolling stock and related rail infrastructure.
- 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: Manutuke Triple: [Gisborne wine region, hasSubregion, Manutuke]
Generated description
Manutuke is a subregion of New Zealand’s Gisborne wine area, known for its viticulture and wine production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Manutuke Target entity description: Manutuke is a subregion of New Zealand’s Gisborne wine area, known for its viticulture and wine production.
-
A.
Maskun
Maskun was an Indonesian politician associated with the nationalist movement and the Indonesian National Party.
-
B.
Mankessim
Mankessim is a major commercial and historical town in Ghana known as an important market center and traditional seat of the Fante people.
-
C.
Mansaka
Mansaka is an Austronesian language spoken by the indigenous Mansaka people of southeastern Mindanao in the Philippines.
-
D.
Tettamanzi
Tettamanzi is an Italian surname most notably associated with Cardinal Dionigi Tettamanzi, a prominent figure in the Roman Catholic Church.
-
E.
Mantena
Mantena is a Norwegian company that specializes in the maintenance and servicing of railway rolling stock and related rail infrastructure.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d73f98dc81909acbb366f00d2d54 |
completed | April 20, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05be59f0088190ae133c2d12beb2c0 |
completed | May 14, 2026, 12:21 p.m. |
| NEDg | Description generation | batch_6a05bf20c800819084e54a34574cb630 |
completed | May 14, 2026, 12:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05bf8bd1cc8190a67b98eb43b4d850 |
completed | May 14, 2026, 12:26 p.m. |
Created at: April 10, 2026, 12:02 p.m.