Triple
T16368813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River God |
E397508
|
entity |
| Predicate | narrator |
P2181
|
FINISHED |
| Object | Taita |
E893968
|
NE 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: Taita | Statement: [River God, narrator, Taita]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taita Context triple: [River God, narrator, Taita]
-
A.
Taita
Taita is a residential suburb in the Hutt Valley region near Wellington, New Zealand.
-
B.
Taita
chosen
The Taita are a Bantu-speaking ethnic group of southeastern Kenya, primarily inhabiting the Taita Hills and known for mixed farming and rich highland cultural traditions.
-
C.
Wilis
Wilis are vengeful female spirits of betrayed brides in the ballet "Giselle," who rise from their graves at night to force men to dance to their deaths.
-
D.
Tibás
Tibás is an urban canton in Costa Rica known for being part of the Greater San José metropolitan area and home to the popular football club Deportivo Saprissa.
-
E.
Seppa
Seppa is a town in the East Kameng district of Arunachal Pradesh in northeastern India, serving as an administrative and cultural center in the Himalayan foothills.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff4021e88190ad093bab74cf82a4 |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0035600420819087c909a615d205a2 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.