Triple
T4863252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Execution of Marie Antoinette |
E108708
|
entity |
| Predicate | hasNotableLocationFeature |
P46334
|
FINISHED |
| Object | near the Tuileries Garden |
—
|
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: near the Tuileries Garden | Statement: [Execution of Marie Antoinette, hasNotableLocationFeature, near the Tuileries Garden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLocationFeature Context triple: [Execution of Marie Antoinette, hasNotableLocationFeature, near the Tuileries Garden]
-
A.
notableLocationFeature
chosen
Indicates that a location is characterized or distinguished by a particular notable physical or contextual feature.
-
B.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
C.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
D.
notableLocation
Indicates that a location is especially significant, prominent, or noteworthy in relation to the subject.
-
E.
notableLocationFeatured
Indicates that a particular location is prominently highlighted or showcased in relation to the subject.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d60e47c819094b5fbe883db4c15 |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.