Triple
T31829090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuanh |
E812475
|
entity |
| Predicate | canCauseConfusionWith |
P2289
|
FINISHED |
| Object | standard pinyin form "Yuan" |
—
|
LITERAL 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: standard pinyin form "Yuan" | Statement: [Yuanh, canCauseConfusionWith, standard pinyin form "Yuan"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canCauseConfusionWith Context triple: [Yuanh, canCauseConfusionWith, standard pinyin form "Yuan"]
-
A.
oftenConfusedWith
chosen
Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
-
B.
renamedToAvoidConfusionWith
Indicates that one entity’s name was changed specifically to prevent it from being mistaken for another entity.
-
C.
historicallyConfusedWith
Indicates that one entity has been mistaken for or identified as another entity in historical records, interpretations, or traditions.
-
D.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
E.
conflictWith
Indicates that two entities are in opposition or disagreement, such that their goals, actions, or states are incompatible or interfere with each other.
- F. None of above.
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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6af8748bc8190bfe1afc840501273 |
completed | May 3, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:47 p.m.