Triple
T31676264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Richter |
E808406
|
entity |
| Predicate | isConsideredCommonNameIn |
P179064
|
FINISHED |
| Object | Germany |
—
|
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: Germany | Statement: [Thomas Richter, isConsideredCommonNameIn, Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isConsideredCommonNameIn Context triple: [Thomas Richter, isConsideredCommonNameIn, Germany]
-
A.
includesCommonName
Indicates that one entity contains or specifies a commonly used (non-scientific) name for another entity.
-
B.
isCommonAsFirstName
Indicates that the referenced name is frequently used as a first (given) name within a specified population or context.
-
C.
isCommonAsMiddleName
Indicates that a given name is frequently used as a middle name rather than as a first or last name.
-
D.
commonName
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
-
E.
commonNameOf
Indicates that one entity is the commonly used or popular name by which the other entity is known.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f719cc31ec819099bebcf833b14d76 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f71995853c8190912025c0e83640c8 |
completed | May 3, 2026, 9:47 a.m. |
Created at: April 30, 2026, 11:03 p.m.