Triple
T4126402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nzaman |
E92734
|
entity |
| Predicate | hasISO639Macrolanguage |
P8719
|
FINISHED |
| Object | Fang (fan) |
E14619
|
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: Fang (fan) | Statement: [Nzaman, hasISO639Macrolanguage, Fang (fan)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fang (fan) Context triple: [Nzaman, hasISO639Macrolanguage, Fang (fan)]
-
A.
Fang
Fang is a Bantu language widely spoken by the Fang people of Central Africa, particularly in Equatorial Guinea, Gabon, and Cameroon.
-
B.
Feng
Feng is a Chinese surname borne by various notable figures in Chinese history and culture.
-
C.
Foxiangge
Foxiangge is the Tower of Buddhist Incense, a prominent multi-story pavilion and iconic landmark within Beijing’s Summer Palace complex.
-
D.
Fang language
chosen
Fang is a Bantu language spoken primarily by the Fang people of Equatorial Guinea, Gabon, and Cameroon, notable for its significant influence on local varieties of Spanish and French.
-
E.
Fumei
Fumei is a given name most notably borne by Mao Fumei, the first wife of Chinese leader Chiang Kai-shek.
- 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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af0219f0e48190b0a925f09d858d65 |
completed | March 9, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b576b96e588190bdf346a66a95138a |
completed | March 14, 2026, 2:54 p.m. |
Created at: March 9, 2026, 3:41 p.m.