Triple
T9598937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economy of Morocco |
E231801
|
entity |
| Predicate | importantSubsector |
P50235
|
FINISHED |
| Object | automotive industry |
—
|
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: automotive industry | Statement: [Economy of Morocco, importantSubsector, automotive industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: importantSubsector Context triple: [Economy of Morocco, importantSubsector, automotive industry]
-
A.
notableSector
chosen
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
B.
majorImport
Indicates that one entity is a primary or significant source of imported goods or resources for another entity.
-
C.
hasSectoralPriority
Indicates that something is designated as having priority or special importance within a particular sector or industry.
-
D.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
E.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
- 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_69ca8484838c8190b2049199d22fef70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a3819608190b3c280f5e1845f85 |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:07 p.m.