Triple
T10934063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Ulis |
E258282
|
entity |
| Predicate | hasPlannedUrbanLayout |
P36957
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Les Ulis, hasPlannedUrbanLayout, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedUrbanLayout Context triple: [Les Ulis, hasPlannedUrbanLayout, true]
-
A.
hasPlannedUrbanCharacter
Indicates that an area exhibits an intentionally designed and organized urban form, layout, and land use pattern rather than informal or unplanned development.
-
B.
hasUrbanPlanning
Indicates that an entity is involved in, responsible for, or characterized by activities or attributes related to urban planning.
-
C.
hasUrbanLayoutType
Indicates that an entity possesses or is characterized by a specific type or pattern of urban spatial layout.
-
D.
isPlannedCity
chosen
Indicates that a city has been deliberately designed and constructed according to a pre-established urban plan rather than developing organically over time.
-
E.
partOfUrbanPlanBy
Indicates that something is included as a component or element within an urban plan created or overseen by a specified agent.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ae073881909720febe9f5f296a |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:23 p.m.