Triple
T11132914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Guise |
E263331
|
entity |
| Predicate | nobleRankInFrance |
P66828
|
FINISHED |
| Object | peer of France |
—
|
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: peer of France | Statement: [Duke of Guise, nobleRankInFrance, peer of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nobleRankInFrance Context triple: [Duke of Guise, nobleRankInFrance, peer of France]
-
A.
nobleRankIn
chosen
Indicates that an entity holds a specified noble rank within a particular political or territorial jurisdiction.
-
B.
rankInLegionOfHonour
Indicates the specific level or grade a person holds within the hierarchy of the Legion of Honour distinction.
-
C.
nobilityClass
Indicates that an entity belongs to, or is associated with, a particular class or rank within a nobility hierarchy.
-
D.
nobilitySystem
Indicates a social or political structure in which individuals are ranked by hereditary titles or noble status.
-
E.
nobleRankInOrder
Indicates that an entity holds a specific noble rank at a particular position within an established order of nobility.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8347a248190837e8c26f25f553a |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.