Triple
T4522358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Wuf |
E103296
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Mr. Wuf |
E103296
|
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: Mr. Wuf | Statement: [Mr. Wuf, shortName, Mr. Wuf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Wuf Context triple: [Mr. Wuf, shortName, Mr. Wuf]
-
A.
Mr. Wuf
chosen
Mr. Wuf is the costumed wolf mascot who represents North Carolina State University's athletic teams and school spirit.
-
B.
Mr. Wong
Mr. Wong is the enigmatic criminal mastermind and primary antagonist in the 1934 mystery film "The Mysterious Mr. Wong."
-
C.
Chi-Fu
Chi-Fu is the pompous and bureaucratic imperial advisor in Disney's 1998 animated film "Mulan," often serving as a comedic antagonist to the protagonist's efforts.
-
D.
Wu
Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
-
E.
Lord Shang
Lord Shang was an influential Chinese statesman and legalist reformer of the Warring States period, best known for transforming the state of Qin into a highly centralized and powerful military state.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd574bd6908190b939d92b5809b101 |
completed | March 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacd4a09881909cf0e9d665454e38 |
completed | March 20, 2026, 8:23 p.m. |
Created at: March 20, 2026, 1:02 p.m.