Triple
T8304357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Napoléon III |
E194424
|
entity |
| Predicate | hasTypeOfToponym |
P82631
|
FINISHED |
| Object | place named after a person |
—
|
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: place named after a person | Statement: [Place Napoléon III, hasTypeOfToponym, place named after a person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfToponym Context triple: [Place Napoléon III, hasTypeOfToponym, place named after a person]
-
A.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
B.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
C.
hasToponymicForm
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
D.
hasToponymicUse
Indicates that a term or name is used as a toponym, i.e., as a place name or geographic designation.
-
E.
hasToponymicQualifier
Indicates that an entity is associated with a specific place-related qualifier (toponym) used to distinguish it from other, similarly named entities.
- F. None of above. chosen
Provenance (4 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e8b9f6081909100d1da8a078616 |
completed | March 31, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69cb70bb3a708190bc705222092da614 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:53 p.m.