Triple
T35698363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hambach, France |
E1031504
|
entity |
| Predicate | hasFormerEmployer |
P1910
|
FINISHED |
| Object | Smart GmbH |
—
|
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: Smart GmbH | Statement: [Hambach, France, hasFormerEmployer, Smart GmbH]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerEmployer Context triple: [Hambach, France, hasFormerEmployer, Smart GmbH]
-
A.
hasPastOccupation
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
B.
formerEmployer
chosen
Indicates that one entity previously employed the other but no longer does so.
-
C.
hasFormerBusiness
Indicates that an entity previously had a business relationship or partnership with another entity, but that relationship is no longer current.
-
D.
hasMajorEmployerHistory
Indicates that an entity has a documented history of employment with a major or significant employer.
-
E.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
Created at: May 3, 2026, 4:05 p.m.