Triple
T8402541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian II, Count Palatine of Zweibrücken-Birkenfeld |
E198408
|
entity |
| Predicate | rankWithinEmpire |
P66828
|
FINISHED |
| Object | Imperial 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: Imperial count | Statement: [Christian II, Count Palatine of Zweibrücken-Birkenfeld, rankWithinEmpire, Imperial count]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankWithinEmpire Context triple: [Christian II, Count Palatine of Zweibrücken-Birkenfeld, rankWithinEmpire, Imperial count]
-
A.
positionOnEmpire
Indicates that one entity holds a specific role, rank, or status within the hierarchical structure of an empire in relation to another entity.
-
B.
rankingInCountry
Indicates the position or level an entity holds within an ordered list specific to a particular country.
-
C.
nobleRankIn
chosen
Indicates that an entity holds a specified noble rank within a particular political or territorial jurisdiction.
-
D.
rankTier
Indicates the classification level or tier assigned to an entity within a ranking or hierarchical system.
-
E.
rankWithinOrganization
Indicates the relative hierarchical position or level an entity holds within a specific organization.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb824efa5c81908ce816cdb8e1fcfb |
completed | March 31, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:04 p.m.