Triple
T37201166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princes of Lippe |
E922039
|
entity |
| Predicate | titleAssumed |
P64388
|
FINISHED |
| Object | Prince of the Holy Roman Empire |
—
|
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: Prince of the Holy Roman Empire | Statement: [Princes of Lippe, titleAssumed, Prince of the Holy Roman Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleAssumed Context triple: [Princes of Lippe, titleAssumed, Prince of the Holy Roman Empire]
-
A.
titleAssumedBy
chosen
Indicates that a particular title or position has been taken on or adopted by a specific entity.
-
B.
titleAffirms
Indicates that a title explicitly asserts, confirms, or supports the truth or validity of a particular claim, idea, or relationship.
-
C.
titleImplies
Indicates that holding or being assigned a particular title suggests or entails a certain role, status, or set of responsibilities.
-
D.
titleThrough
Indicates a relationship where one entity holds or is identified by a specific title by means of, or via the mediation of, another entity or context.
-
E.
titleInPretence
Indicates that an entity holds a specific title or role within a fictional, staged, or pretended context rather than in reality.
- 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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4:15 p.m.