Triple
T1324742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Canino and Musignano |
E28299
|
entity |
| Predicate | titleUse |
P10405
|
FINISHED |
| Object | courtesy and dynastic title |
—
|
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: courtesy and dynastic title | Statement: [Prince of Canino and Musignano, titleUse, courtesy and dynastic title]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleUse Context triple: [Prince of Canino and Musignano, titleUse, courtesy and dynastic title]
-
A.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
B.
usesTitle
chosen
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
C.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
-
D.
titleType
Indicates the specific category or kind of title associated with an entity (e.g., whether it is a main title, alternative title, working title, etc.).
-
E.
titlePhrase
Indicates that one entity is a phrase functioning as the title or name of 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19e81c0819092f85201ae34422a |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.