Triple
T36069165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple de la Sibylle |
E1043316
|
entity |
| Predicate | parkCreatedUnder |
P184546
|
FINISHED |
| Object | Napoleon III |
—
|
NE NERFINISHED |
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: Napoleon III | Statement: [Temple de la Sibylle, parkCreatedUnder, Napoleon III]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkCreatedUnder Context triple: [Temple de la Sibylle, parkCreatedUnder, Napoleon III]
-
A.
parkFeature
Indicates that a particular feature, amenity, or element is part of, located within, or characteristic of a park.
-
B.
createdAsPublicPark
Indicates that something was originally established or designated for use as a public park.
-
C.
parkType
Indicates the specific category or classification of a park based on its designated use, management, or characteristics.
-
D.
parkSide
Indicates that one entity is located on the side of or adjacent to a park relative to another reference point or area.
-
E.
placeCreated
Indicates that one entity is the location where another entity was created or came into existence.
- 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_69f76e2fd3248190b900d9a492bf5a7a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b35e32d481909ef0220e6f6ff4a8 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2c66054819083897e25edb65ba7 |
completed | May 3, 2026, 8:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.