Triple
T4417469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquis de Lafayette statue (Paris, Cours-la-Reine) |
E95009
|
entity |
| Predicate | sculptorNationality |
P55538
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Marquis de Lafayette statue (Paris, Cours-la-Reine), sculptorNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sculptorNationality Context triple: [Marquis de Lafayette statue (Paris, Cours-la-Reine), sculptorNationality, American]
-
A.
hasSculptor
Indicates that one entity serves as the sculptor (creator of a sculpture) of another entity.
-
B.
assistantSculptor
Indicates a relationship where one entity serves as an assistant to another entity in the role or activity of sculpting.
-
C.
sculptorOfFrontStatue
Indicates that one entity is the sculptor who created the statue located at the front of another entity (such as a building or site).
-
D.
designerNationality
Indicates that a designer has a specific national or country affiliation.
-
E.
architecturalSculptor
Indicates a relationship where a person serves as the sculptor responsible for the sculptural elements of an architectural work or structure.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551d5d7481908528c2de0a6fda06 |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.