Triple
T445720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince William of Orange (disputed) |
E7013
|
entity |
| Predicate | nameUsedIn |
P13305
|
FINISHED |
| Object | toponymic attributions in the United States |
—
|
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: toponymic attributions in the United States | Statement: [Prince William of Orange (disputed), nameUsedIn, toponymic attributions in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameUsedIn Context triple: [Prince William of Orange (disputed), nameUsedIn, toponymic attributions in the United States]
-
A.
nameUsedBy
Indicates that a particular name is employed or referenced by a specific entity.
-
B.
nameUsedToAvoid
Indicates that one entity uses a particular name or designation in order to avoid another entity or an unwanted situation involving that entity.
-
C.
nameUsedToAccommodate
Indicates that a particular name was previously used to refer to or accommodate an entity, but is no longer its current or primary name.
-
D.
nameOf
Indicates that one entity is the name or designation of another entity.
-
E.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef479ec08190a659eead6eb0d4d0 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2eddfb5508190a4e06e1b260d8b2b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.