Triple
T30221127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | censor (Roman Republic) |
E768346
|
entity |
| Predicate | rankInCursusHonorum |
P175250
|
FINISHED |
| Object | above consul |
—
|
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: above consul | Statement: [censor (Roman Republic), rankInCursusHonorum, above consul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInCursusHonorum Context triple: [censor (Roman Republic), rankInCursusHonorum, above consul]
-
A.
rankInLegionOfHonour
Indicates the specific level or grade a person holds within the hierarchy of the Legion of Honour distinction.
-
B.
honorRank
chosen
Indicates a hierarchical relationship where one entity holds a particular level or position of honor or prestige relative to others.
-
C.
rankComparedToLegionOfHonour
Indicates how the rank or level associated with something compares to the corresponding rank within the French Legion of Honour system.
-
D.
nobleRankIn
Indicates that an entity holds a specified noble rank within a particular political or territorial jurisdiction.
-
E.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
- 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 29, 2026, 7:35 p.m.