Triple
T9693981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wallmapu |
E234601
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Ngulu Mapu
Ngulu Mapu is the eastern, Argentine sector of the ancestral Mapuche territory within the broader region known as Wallmapu.
|
E815775
|
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: Ngulu Mapu | Statement: [Wallmapu, hasPart, Ngulu Mapu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ngulu Mapu Context triple: [Wallmapu, hasPart, Ngulu Mapu]
-
A.
Ralamuli
Ralamuli is an alternate name for the Rarámuri language spoken by the Indigenous Rarámuri (Tarahumara) people of northern Mexico.
-
B.
Mata Khivi
Mata Khivi was a revered Sikh figure known for her service, compassion, and role in developing the tradition of the Guru ka Langar (community kitchen).
-
C.
Mazabuka
Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
-
D.
Maroelap
Maroelap is the former name of Maloelap Atoll, a coral atoll in the Ratak Chain of the Marshall Islands in the central Pacific Ocean.
-
E.
Bassa Langa
Bassa Langa is the southern, lower-lying part of Italy’s Langhe area, known for its rolling hills, vineyards, and traditional Piedmontese wine and food culture.
- 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: Ngulu Mapu Triple: [Wallmapu, hasPart, Ngulu Mapu]
Generated description
Ngulu Mapu is the eastern, Argentine sector of the ancestral Mapuche territory within the broader region known as Wallmapu.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ngulu Mapu Target entity description: Ngulu Mapu is the eastern, Argentine sector of the ancestral Mapuche territory within the broader region known as Wallmapu.
-
A.
Ralamuli
Ralamuli is an alternate name for the Rarámuri language spoken by the Indigenous Rarámuri (Tarahumara) people of northern Mexico.
-
B.
Mata Khivi
Mata Khivi was a revered Sikh figure known for her service, compassion, and role in developing the tradition of the Guru ka Langar (community kitchen).
-
C.
Mazabuka
Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
-
D.
Maroelap
Maroelap is the former name of Maloelap Atoll, a coral atoll in the Ratak Chain of the Marshall Islands in the central Pacific Ocean.
-
E.
Bassa Langa
Bassa Langa is the southern, lower-lying part of Italy’s Langhe area, known for its rolling hills, vineyards, and traditional Piedmontese wine and food culture.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d348868819083aec7a5da8c455b |
completed | April 1, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1911d33f081908637cbf4c1949bcd |
completed | April 4, 2026, 10:30 p.m. |
| NEDg | Description generation | batch_69d19533ef1c8190926ffb4eb92b8ef4 |
completed | April 4, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d195b69a4c8190941b92cc36bdc416 |
completed | April 4, 2026, 10:50 p.m. |
Created at: March 30, 2026, 8:17 p.m.