Triple
T38428104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parisian Plaine |
E903417
|
entity |
| Predicate | hasUrbanSprawlFrom |
P161692
|
FINISHED |
| Object | Paris |
—
|
NE NERFINISHED |
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: Paris | Statement: [Parisian Plaine, hasUrbanSprawlFrom, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanSprawlFrom Context triple: [Parisian Plaine, hasUrbanSprawlFrom, Paris]
-
A.
hasUrbanExpansionTo
chosen
Indicates that an urban area has expanded or extended its development into another specified area or region.
-
B.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
C.
isUrbanizing
Indicates a process in which an area or population becomes more urban in character, typically through increased development, infrastructure, and concentration of people and activities.
-
D.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
E.
hasUrbanGrowthCharacteristic
Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.