Triple
T13565817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Marly |
E324030
|
entity |
| Predicate | guestSelection |
P110101
|
FINISHED |
| Object | small invited court |
—
|
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: small invited court | Statement: [Château de Marly, guestSelection, small invited court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: guestSelection Context triple: [Château de Marly, guestSelection, small invited court]
-
A.
holderSelection
Indicates that a particular entity has been chosen or designated to serve as the holder of another entity or resource.
-
B.
venueSelection
Indicates the relationship in which a specific venue is chosen or designated for an event, activity, or purpose among available options.
-
C.
guestFlow
Indicates the movement or progression of guests through a space, process, or experience over time.
-
D.
typicalHostSelection
Indicates the usual or preferred choice of host entity that is selected in a given context or process.
-
E.
chairSelectedFrom
Indicates that a particular chair has been chosen from a larger set or collection of chairs.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00cecd48190a9a2caff3d424817 |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf7fefa881908471f1400f813ccc |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:48 p.m.