Triple
T29787321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marais |
E756298
|
entity |
| Predicate | urbanPlanningEvent |
P91028
|
FINISHED |
| Object | subject to Malraux heritage protection laws |
—
|
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: subject to Malraux heritage protection laws | Statement: [Marais, urbanPlanningEvent, subject to Malraux heritage protection laws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanPlanningEvent Context triple: [Marais, urbanPlanningEvent, subject to Malraux heritage protection laws]
-
A.
associatedCityEvent
Indicates a relationship where a city is linked to, involved in, or serves as the location for a particular event.
-
B.
urbanPlanningFunction
Indicates a functional role or purpose that something serves within the planning, organization, or management of urban spaces and infrastructure.
-
C.
eventManagement
Indicates the organization, coordination, and oversight of all activities and resources involved in planning and executing an event.
-
D.
mainEventCity
Indicates the city in which the primary or main event takes place.
-
E.
urbanPlanningTheme
chosen
Indicates a thematic relationship in which an entity is concerned with, addresses, or is categorized under topics related to urban planning.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 5:09 p.m.