Triple
T15471844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Île aux Cygnes |
E376678
|
entity |
| Predicate | statueGiftFrom |
P23811
|
FINISHED |
| Object | French community 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: French community in the United States | Statement: [Île aux Cygnes, statueGiftFrom, French community in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statueGiftFrom Context triple: [Île aux Cygnes, statueGiftFrom, French community in the United States]
-
A.
statueName
Indicates that a statue has a specific name or title associated with it.
-
B.
statuesBy
Indicates that one entity is the creator, sculptor, or originator of statues depicting or associated with another entity.
-
C.
topStatue
Indicates that one entity is positioned as a statue on top of another entity.
-
D.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
E.
giftedBy
chosen
Indicates that one entity has given or presented another entity as a gift to a recipient.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6c57308190b4cfe661c26addd4 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:33 a.m.