Triple
T27992765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xu |
E706924
|
entity |
| Predicate | hasSurnameRank |
P192047
|
FINISHED |
| Object | common Chinese surname |
—
|
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: common Chinese surname | Statement: [Xu, hasSurnameRank, common Chinese surname]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurnameRank Context triple: [Xu, hasSurnameRank, common Chinese surname]
-
A.
hasSurnameFrequency
Indicates that a surname occurs with a specified frequency or rate within a given population or dataset.
-
B.
hasSurnamePrefix
Indicates that one entity’s surname begins with, or is prefixed by, the string or component specified by the other entity.
-
C.
hasSurnameType
Indicates that an entity’s surname belongs to a particular category or type (e.g., patronymic, toponymic, occupational).
-
D.
isSurname
Indicates that one entity is the family name (last name) of another entity.
-
E.
hasSurnameFrequencyReason
Indicates the reason or explanation for the frequency with which a particular surname occurs.
- F. None of above. chosen
Provenance (4 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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69fcf36bb86c8190a0a0ccf47cb56e5c |
completed | May 7, 2026, 8:17 p.m. |
Created at: April 27, 2026, 7:51 p.m.