Triple
T12991038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman of Steel |
E321905
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Yeba |
E763077
|
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: Yeba | Statement: [Woman of Steel, hasPart, Yeba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yeba Context triple: [Woman of Steel, hasPart, Yeba]
-
A.
Yeba
chosen
Yeba are ritual specialists of the Limbu people who conduct traditional religious ceremonies, healing rites, and spiritual mediation within their indigenous belief system.
-
B.
Bisha
Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
-
C.
Jebba
Jebba is a town in western Nigeria known for its strategic location on the Niger River and its historic bridge linking northern and southern Nigeria.
-
D.
Yinjebi
Yinjebi is an alternative name for the Nzebi people, a Bantu ethnic group primarily living in Gabon and the Republic of the Congo.
-
E.
Taybad
Taybad is a city in northeastern Iran near the Afghan border, known as a local commercial and transit hub within Razavi Khorasan Province.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7765788190a9503ef055bc30ca |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8fb70f481908a9a4ca04d6bf93b |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 8:43 p.m.