Triple
T11092656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Église Saint-Nicolas-du-Chardonnet |
E262293
|
entity |
| Predicate | occupiedSince |
P3418
|
FINISHED |
| Object | 1977 |
—
|
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: 1977 | Statement: [Église Saint-Nicolas-du-Chardonnet, occupiedSince, 1977]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiedSince Context triple: [Église Saint-Nicolas-du-Chardonnet, occupiedSince, 1977]
-
A.
occupiedFrom
chosen
Indicates that an entity is in use or inhabited starting from a specified point in time.
-
B.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
C.
occupies
Indicates that one entity takes up or resides within a physical or conceptual space belonging to or associated with another entity.
-
D.
wasOccupiedDuring
Indicates that an entity was under the control, presence, or use of another entity throughout a specified time period.
-
E.
hasOccupancyStatus
Indicates the current usage or availability state of something, such as whether it is occupied, vacant, or otherwise in use.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ec6564819097624195d0cd9093 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.