Triple
T34927017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayeb Benamara |
E1007316
|
entity |
| Predicate | locatedInTheMetropolitanRegionGoverned |
P108274
|
FINISHED |
| Object | Île-de-France |
E6961
|
NE 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: Île-de-France | Statement: [Tayeb Benamara, locatedInTheMetropolitanRegionGoverned, Île-de-France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTheMetropolitanRegionGoverned Context triple: [Tayeb Benamara, locatedInTheMetropolitanRegionGoverned, Île-de-France]
-
A.
belongsToMetropolitanRegion
chosen
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
B.
locatedNearMetropolitanArea
Indicates that one entity is situated in close geographic proximity to a metropolitan (urban) area.
-
C.
isMunicipalityInRegion
Indicates that a municipality is located within and administratively belongs to a specific region.
-
D.
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.
-
E.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
- F. None of above.
Provenance (4 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_69f76dc3d83881909d5c3c14455cfa2c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37bcf9364c8190a489e33feb53a553 |
completed | June 21, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.