Triple
T20757176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LFSB |
E510878
|
entity |
| Predicate | hasFrenchCustomsSector |
P141385
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [LFSB, hasFrenchCustomsSector, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrenchCustomsSector Context triple: [LFSB, hasFrenchCustomsSector, true]
-
A.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
B.
usesPrimaryFrenchGateway
Indicates that an entity routes its primary communications or connections through a main gateway located in or associated with French infrastructure or networks.
-
C.
hasCustomsAgency
Indicates that an entity is associated with or overseen by a specific customs agency responsible for regulating and controlling cross-border goods and related activities.
-
D.
hasCustomsUnion
Indicates that two or more entities participate in a customs union, sharing a common external tariff and removing customs duties between them.
-
E.
reservedToFrance
Indicates that something is exclusively allocated or designated for France.
- F. None of above. chosen
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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c23113c88190a567c3a098cf7552 |
completed | April 21, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:35 p.m.