Triple
T28793783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Confluentes |
E727029
|
entity |
| Predicate | influencedModernToponym |
P98810
|
FINISHED |
| Object | Koblenz |
—
|
NE NERFINISHED |
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: Koblenz | Statement: [Confluentes, influencedModernToponym, Koblenz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedModernToponym Context triple: [Confluentes, influencedModernToponym, Koblenz]
-
A.
influenceOnToponymy
chosen
Indicates that one entity has affected or shaped the naming, form, or development of place names associated with another entity.
-
B.
toponymReflects
Indicates that a place name embodies, mirrors, or expresses some characteristic, feature, or aspect of the place it denotes.
-
C.
hasToponymicMotivation
Indicates that something is motivated, derived, or named based on a place name (toponym).
-
D.
legacyToponym
Indicates that one place name is an older or former name historically used to refer to the same geographic entity as another place name.
-
E.
usedAsToponymicBy
Indicates that one entity is employed as a place-based surname or name-forming element for another entity.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 28, 2026, 6:24 a.m.