Triple
T5119065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuwa |
E115414
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Nini |
E85207
|
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: Nini | Statement: [Fuwa, member, Nini]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nini Context triple: [Fuwa, member, Nini]
-
A.
Nini
chosen
Nini is one of the five Fuwa mascots of the 2008 Beijing Summer Olympics, inspired by a swallow and symbolizing good luck and the host city's culture.
-
B.
Nini
Nini is a supporting character in *Moulin Rouge! The Musical*, portrayed as one of the club’s dancers and a confidante within the bohemian world of the Moulin Rouge.
-
C.
Mishanya
Mishanya is a Russian diminutive nickname commonly used for the male given name Mikhail.
-
D.
Ano Mera
Ano Mera is a traditional inland village on the Greek island of Mykonos, known for its quieter atmosphere, central square, and historic Panagia Tourliani monastery.
-
E.
Jeena
Jeena is the central protagonist of the Indian television series "Good Vibes."
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd77cf6590819081488b739efae32c |
completed | March 20, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4a6a7988190b9beec3f0d9494d1 |
completed | March 21, 2026, 4:17 p.m. |
Created at: March 20, 2026, 1:42 p.m.