Triple
T31648166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graf von Hohenstein |
E807638
|
entity |
| Predicate | equivalentRankInEnglish |
P173433
|
FINISHED |
| Object | Count |
—
|
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: Count | Statement: [Graf von Hohenstein, equivalentRankInEnglish, Count]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentRankInEnglish Context triple: [Graf von Hohenstein, equivalentRankInEnglish, Count]
-
A.
rankEquivalent
Indicates that two entities hold the same rank or hierarchical level within a given ordering or classification system.
-
B.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
C.
equivalentRankInArmy
Indicates that two entities hold military positions considered to be of the same rank or level within their respective armies.
-
D.
equivalentGivenNameInEnglish
Indicates that two given names are equivalent in meaning or usage when expressed in English.
-
E.
equivalentEnglishForm
chosen
Indicates that two expressions share the same meaning in English, serving as equivalent linguistic forms.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b967d5308190bbb66d0a8dd52612 |
completed | May 3, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 30, 2026, 10:52 p.m.