Triple
T14998729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chagga people |
E374025
|
entity |
| Predicate | mbege |
P116285
|
FINISHED |
| Object | banana beer |
—
|
LITERAL FINISHED |
How this triple was built (2 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: banana beer | Statement: [Chagga people, mbege, banana beer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mbege Context triple: [Chagga people, mbege, banana beer]
-
A.
metBetween
Indicates that two or more entities had an in-person or virtual meeting or encounter with each other during a specified time or context.
-
B.
metOn
Indicates that two or more entities encountered each other at the same time and place for the first time or for a particular meeting.
-
C.
mayFace
Indicates that an entity is likely or permitted to encounter, experience, or be subjected to another entity or situation.
-
D.
מטרה
Indicates that an entity serves as the goal, aim, or intended target of another entity or action.
-
E.
maimed
Indicates that one entity has caused another to suffer severe, permanent physical injury or disfigurement.
- F. None of above. chosen
Provenance (4 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded71a5618819083ae96a79735ef98 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:54 a.m.