Triple
T10699531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waorani people |
E252234
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object |
Waodani
Waodani are an Indigenous people of the Ecuadorian Amazon rainforest known for their traditional semi-nomadic lifestyle and deep connection to their forest environment.
|
E881522
|
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: Waodani | Statement: [Waorani people, nativeName, Waodani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waodani Context triple: [Waorani people, nativeName, Waodani]
-
A.
Godan
Godan is a landmark Hindi novel by Munshi Premchand that portrays the struggles of Indian peasants under social and economic oppression.
-
B.
Wotho
Wotho is a small inhabited island in the Marshall Islands that serves as the main settlement and administrative center of Wotho Atoll.
-
C.
Òdena
Òdena is a municipality in the Anoia comarca of Catalonia, Spain, known for its rural landscape and proximity to the town of Igualada.
-
D.
Wihro
Wihro is the official mascot character created for the 2022 Mediterranean Games.
-
E.
Oederan
Oederan is a small historic town in the Free State of Saxony in eastern Germany, known for its traditional architecture and model railway park.
- 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: Waodani Triple: [Waorani people, nativeName, Waodani]
Generated description
Waodani are an Indigenous people of the Ecuadorian Amazon rainforest known for their traditional semi-nomadic lifestyle and deep connection to their forest environment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waodani Target entity description: Waodani are an Indigenous people of the Ecuadorian Amazon rainforest known for their traditional semi-nomadic lifestyle and deep connection to their forest environment.
-
A.
Godan
Godan is a landmark Hindi novel by Munshi Premchand that portrays the struggles of Indian peasants under social and economic oppression.
-
B.
Wotho
Wotho is a small inhabited island in the Marshall Islands that serves as the main settlement and administrative center of Wotho Atoll.
-
C.
Òdena
Òdena is a municipality in the Anoia comarca of Catalonia, Spain, known for its rural landscape and proximity to the town of Igualada.
-
D.
Wihro
Wihro is the official mascot character created for the 2022 Mediterranean Games.
-
E.
Oederan
Oederan is a small historic town in the Free State of Saxony in eastern Germany, known for its traditional architecture and model railway park.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd8abd7c81909c274aa1699a3695 |
completed | April 9, 2026, 1:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbad110d9481908c3c0873424ec616 |
completed | April 12, 2026, 2:32 p.m. |
| NEDg | Description generation | batch_69dbaeb211088190a9118c71918584e5 |
completed | April 12, 2026, 2:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbaf7c999c819097a8cdf5bd82f648 |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 8, 2026, 9:12 p.m.