Triple
T27871803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 熊氏 |
E704508
|
entity |
| Predicate | hasEtymologicalCategory |
P125565
|
FINISHED |
| Object | surnames from animals or totems |
—
|
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: surnames from animals or totems | Statement: [熊氏, hasEtymologicalCategory, surnames from animals or totems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEtymologicalCategory Context triple: [熊氏, hasEtymologicalCategory, surnames from animals or totems]
-
A.
hasEtymologicalBasis
Indicates that one term, name, or expression is derived from, based on, or historically formed from the other in terms of linguistic origin.
-
B.
hasEtymologyConcept
Indicates that something derives its origin, form, or meaning from a particular etymological concept or source.
-
C.
etymologicalClass
chosen
Indicates the relationship between a term and the category or type of its origin or historical linguistic development.
-
D.
hasEtymologyDetail
Indicates a relationship where additional explanatory or contextual information about the origin or derivation of a term is provided.
-
E.
hasLatinEtymology
Indicates that something originates from or is derived from a Latin word or linguistic root.
- 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 27, 2026, 6:25 p.m.