Triple
T2403448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maasai language |
E50220
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Maa
Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
|
E262862
|
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: Maa | Statement: [Maasai language, hasAlternativeName, Maa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maa Context triple: [Maasai language, hasAlternativeName, Maa]
-
A.
Terra
Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
-
B.
Verden
Verden is a historic town in Lower Saxony, Germany, known for its medieval cathedral and location along the Weser River.
-
C.
Tera
Tera is a West Chadic language spoken primarily in northeastern Nigeria by the Tera people.
-
D.
Urana
Urana is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural surroundings and historic country character.
-
E.
Mapun
Mapun is an Austronesian language spoken primarily by the Mapun people of the southern Philippines, particularly on Mapun (Cagayan de Sulu) Island in the Sulu Sea.
- 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: Maa Triple: [Maasai language, hasAlternativeName, Maa]
Generated description
Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maa Target entity description: Maa is a Nilotic language spoken primarily by the Maasai people of Kenya and Tanzania.
-
A.
Terra
Terra is a sustainability-themed character created as one of the official mascots for Expo 2020 Dubai, symbolizing environmental awareness and ecological responsibility.
-
B.
Verden
Verden is a historic town in Lower Saxony, Germany, known for its medieval cathedral and location along the Weser River.
-
C.
Tera
Tera is a West Chadic language spoken primarily in northeastern Nigeria by the Tera people.
-
D.
Urana
Urana is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural surroundings and historic country character.
-
E.
Mapun
Mapun is an Austronesian language spoken primarily by the Mapun people of the southern Philippines, particularly on Mapun (Cagayan de Sulu) Island in the Sulu Sea.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8f8aa2881909192920ee394f0b3 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3e740c88190872aa1a7834d73b0 |
completed | March 9, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_69aeb4b942b08190addc2885fbda0e41 |
completed | March 9, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeb557247c8190920ce3a5db388800 |
completed | March 9, 2026, 11:56 a.m. |
Created at: March 4, 2026, 7:58 p.m.