Triple
T32830617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Saint-Charles |
E839677
|
entity |
| Predicate | chancery |
P62953
|
FINISHED |
| Object | Chancellery of the Orders of Monaco |
—
|
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: Chancellery of the Orders of Monaco | Statement: [Order of Saint-Charles, chancery, Chancellery of the Orders of Monaco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chancery Context triple: [Order of Saint-Charles, chancery, Chancellery of the Orders of Monaco]
-
A.
hasChancery
chosen
Indicates that an entity possesses or is associated with a chancery, i.e., an official office or administrative body responsible for formal documents and records.
-
B.
lordChancellor
Indicates that one entity holds the position or role of Lord Chancellor in relation to another entity (such as a state, monarch, or government).
-
C.
hasChancel
Indicates that something possesses or includes a chancel as part of its structure or layout.
-
D.
lordPrivySeal
Indicates that an entity holds or is associated with the governmental office or role of Lord Privy Seal.
-
E.
laterChamber
Indicates that one chamber occurs or is situated at a later point in a sequence or process relative to another chamber.
- 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_69f3493f22f88190ae6dd4bc15b6cf8d |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce6d659881909ddcec1d2966e020 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:16 a.m.