Triple
T10977912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flecher |
E259420
|
entity |
| Predicate | hasTraditionalMeaning |
P39675
|
FINISHED |
| Object | maker of arrows |
—
|
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: maker of arrows | Statement: [Flecher, hasTraditionalMeaning, maker of arrows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalMeaning Context triple: [Flecher, hasTraditionalMeaning, maker of arrows]
-
A.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
B.
hasTraditionalInterpretation
chosen
Indicates that something is associated with or understood according to a long-established or customary interpretation.
-
C.
hasTraditionalSymbol
Indicates that something is associated with or represented by a conventional or culturally established symbol.
-
D.
hasTraditionalTranslation
Indicates that one entity serves as the established or customary translation of another entity in a traditional or historically accepted sense.
-
E.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771f6a9448190b3932ee801ae0da9 |
completed | April 9, 2026, 9:31 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.