Triple
T31988586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourbon-Vendée |
E816801
|
entity |
| Predicate | toponymReflects |
P173086
|
FINISHED |
| Object | royalist allegiance |
—
|
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: royalist allegiance | Statement: [Bourbon-Vendée, toponymReflects, royalist allegiance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toponymReflects Context triple: [Bourbon-Vendée, toponymReflects, royalist allegiance]
-
A.
toponymRefersTo
Indicates that a place name (toponym) designates or refers to a specific geographic entity or location.
-
B.
includesToponym
Indicates that one entity contains or references a place name (toponym) associated with another entity.
-
C.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
D.
toponymLiteralMeaning
Indicates the literal or etymological meaning of a place name (toponym), describing what the name directly translates to or signifies.
-
E.
legacyToponym
Indicates that one place name is an older or former name historically used to refer to the same geographic entity as another place name.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b3b2d2288190b8ef79a173313e59 |
completed | May 3, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:12 a.m.