Triple
T26391150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dinner Party |
E663414
|
entity |
| Predicate | numberOfPlaceSettings |
P33015
|
FINISHED |
| Object | 39 |
—
|
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: 39 | Statement: [The Dinner Party, numberOfPlaceSettings, 39]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlaceSettings Context triple: [The Dinner Party, numberOfPlaceSettings, 39]
-
A.
hasPlaceSetting
Indicates that a dining-related entity is associated with a specific arrangement of tableware and utensils prepared for an individual at a table.
-
B.
numberOfVenues
Indicates the total count of venues associated with a given entity or context.
-
C.
numberOfPlacements
Indicates the total count of times an entity has been placed or assigned within a given context or system.
-
D.
numberOfPlates
chosen
Indicates the quantity of plates associated with or involved in a particular entity, event, or context.
-
E.
totalPlaces
Indicates the total number of distinct places associated with or involved in the given context or entity.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
Created at: April 26, 2026, 11:26 p.m.