Triple
T17591993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mémorial de Caen |
E428470
|
entity |
| Predicate | visitorStatisticsRecord |
P427
|
FINISHED |
| Object | over 400000 visitors per year |
—
|
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: over 400000 visitors per year | Statement: [Mémorial de Caen, visitorStatisticsRecord, over 400000 visitors per year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitorStatisticsRecord Context triple: [Mémorial de Caen, visitorStatisticsRecord, over 400000 visitors per year]
-
A.
visitorCount
chosen
Indicates the number of visitors associated with a particular entity, context, or time period.
-
B.
visitorStatus
Indicates the current state or condition of an entity in its role as a visitor (e.g., whether they are active, pending, past, or otherwise classified in their visit).
-
C.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
D.
visitorScore
Indicates the number of points or goals scored by the visiting/away participant in a game or contest.
-
E.
visitorIs
Indicates that one entity is acting in the role or capacity of a visitor with respect to another 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469e79dac8190953a1ce8fc015b20 |
completed | April 19, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:51 a.m.