Triple
T13438779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hôtel de Crillon |
E320298
|
entity |
| Predicate | convertedToHotel |
P109933
|
FINISHED |
| Object | 1909 |
—
|
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: 1909 | Statement: [Hôtel de Crillon, convertedToHotel, 1909]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convertedToHotel Context triple: [Hôtel de Crillon, convertedToHotel, 1909]
-
A.
hadStationHotel
Indicates that a railway station possessed or was associated with a hotel facility serving its passengers or operations.
-
B.
convertedAttractionTo
Indicates that one entity has transformed or redirected its romantic or emotional attraction from one target to another.
-
C.
closedAsHotel
Indicates that an establishment ceased operating in general and specifically stopped functioning as a hotel.
-
D.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
E.
convertedBy
Indicates that one entity has been transformed or changed in form, state, or representation through the action or process performed by another entity.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee5ec488190bd0c1e990dbd2bc2 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.