Triple
T28414674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chén Píng |
E719767
|
entity |
| Predicate | canBeMaleName |
P187571
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chén Píng, canBeMaleName, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeMaleName Context triple: [Chén Píng, canBeMaleName, true]
-
A.
canBeMiddleName
Indicates that one entity is suitable or allowed to serve as the middle name of another entity.
-
B.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
C.
canBeLegalGivenName
Indicates that a given name satisfies the rules or conditions required to be considered legally valid.
-
D.
canBeGivenNameOnItsOwn
Indicates that something is acceptable or valid to be used as a standalone given name without needing additional components.
-
E.
canBeFictionalCharacterName
Indicates that something is suitable or valid to be used as the name of a fictional character.
- 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb6fdab95c81909acff3c6a2359787 |
completed | May 6, 2026, 4:44 p.m. |
Created at: April 28, 2026, 1:29 a.m.