Triple
T23797240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campus de Menton de Sciences Po |
E588571
|
entity |
| Predicate | targetRegionForRecruitment |
P50747
|
FINISHED |
| Object | Middle East |
—
|
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: Middle East | Statement: [Campus de Menton de Sciences Po, targetRegionForRecruitment, Middle East]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetRegionForRecruitment Context triple: [Campus de Menton de Sciences Po, targetRegionForRecruitment, Middle East]
-
A.
eligibleRegion
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
-
B.
registrationRegion
Indicates the geographic or administrative region in which an entity is officially registered.
-
C.
typicalTargetRegion
Indicates the region or area that an action, process, or effect is most commonly directed toward or occurs in.
-
D.
campaignRegion
chosen
Indicates the geographic area or territory in which a campaign is conducted or targeted.
-
E.
exportRegion
Indicates the region or geographic area from which goods, services, or resources are exported.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c6ddc2d88190b6124d9fb2695d24 |
completed | April 29, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:50 p.m.