Triple
T29127458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris region, France |
E738270
|
entity |
| Predicate | hasMetropolitanAreaCenteredOn |
P20617
|
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: [Paris region, France, hasMetropolitanAreaCenteredOn, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetropolitanAreaCenteredOn Context triple: [Paris region, France, hasMetropolitanAreaCenteredOn, Paris]
-
A.
hasPopulationCenter
Indicates that an area, region, or administrative unit contains or is served by a primary settlement or population hub.
-
B.
isMetropolitanOf
Indicates that one entity is the primary metropolitan area or major urban center associated with another entity, such as a region, country, or administrative division.
-
C.
isMetropolitanCoreOf
chosen
Indicates that one area functions as the central, most urbanized core within a larger metropolitan region or system.
-
D.
metropolitanOf
Indicates that one place serves as the primary metropolitan center or core urban area for another place or region.
-
E.
hasPopulationCenterType
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
- 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_69f07cb29cdc8190afa55444553de60c |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 28, 2026, 11:29 a.m.