Triple
T16681145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nie (Kaifeng Jewish surname) |
E405340
|
entity |
| Predicate | hasRomanization |
P2508
|
FINISHED |
| Object | Nie |
E784262
|
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: Nie | Statement: [Nie (Kaifeng Jewish surname), hasRomanization, Nie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nie Context triple: [Nie (Kaifeng Jewish surname), hasRomanization, Nie]
-
A.
Nie
chosen
Nie is the surname of Norman H. Nie, an American political scientist and co-creator of the SPSS statistical software package.
-
B.
Nu
Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
-
C.
Neo
Neo is the protagonist of the science fiction film series "The Matrix," a hacker who becomes humanity's prophesied savior within a simulated reality.
-
D.
Nic
Nic is an entity characterized in opposition to "Mc," suggesting it embodies contrasting qualities, roles, or attributes within their shared context.
-
E.
Nic
Nic is one of the two lesbian mothers in the film "The Kids Are All Right," portrayed as a responsible, controlling physician whose family life is disrupted when her children seek out their sperm-donor father.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6f5cf481909e7628bbaa884e5a |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a404f448190a9dc7831382ffcdc |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.