Triple
T19791611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pont de Mirabeau |
E475423
|
entity |
| Predicate | dateClassementMonumentHistorique |
P62039
|
FINISHED |
| Object | 1975 |
—
|
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: 1975 | Statement: [Pont de Mirabeau, dateClassementMonumentHistorique, 1975]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateClassementMonumentHistorique Context triple: [Pont de Mirabeau, dateClassementMonumentHistorique, 1975]
-
A.
hasNumberOfMonuments
Indicates the specific count of monuments associated with or present in a given entity.
-
B.
yearOfMonument
Indicates the specific year in which a monument was established, built, or officially dedicated.
-
C.
majorInscriptionSite
Indicates that a location serves as a primary or significant site where inscriptions are prominently found or produced.
-
D.
chronologyCriterion
Indicates that one entity is used as a temporal reference or ordering basis for another, establishing their relative position in time.
-
E.
historicalDesignation
chosen
Indicates that an entity has been formally assigned a particular status, title, or classification based on its historical significance.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c37a3c819080f195d58adaaa7b |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e53053ed2881908400becdfada7fd3 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:49 p.m.