Triple
T5910960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | harpe sword |
E131455
|
entity |
| Predicate | termVariant |
P4680
|
FINISHED |
| Object | harpe |
—
|
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: harpe | Statement: [harpe sword, termVariant, harpe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termVariant Context triple: [harpe sword, termVariant, harpe]
-
A.
variant
chosen
Indicates that one entity is an alternative form, version, or variation of another entity.
-
B.
termType
Indicates the classification or category of a term within a system, specifying what kind of term it is (e.g., type, role, or function) in relation to others.
-
C.
termVariesBy
Indicates that the value or meaning of a term changes depending on a specified factor, such as context, dimension, or condition.
-
D.
brandNameVariant
Indicates that one brand name is an alternative or variant form of another brand name, such as a spelling, regional, or stylistic variation.
-
E.
termAlsoUsedFor
Indicates that one term is also used to refer to the same or closely related concept as another term.
- 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c048fc112c8190b905bf561c9de096 |
completed | March 22, 2026, 7:54 p.m. |
| PD | Predicate disambiguation | batch_69c03352208c8190968efed05a9fd416 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.