Triple
T16084463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adrian Dalsey |
E390191
|
entity |
| Predicate | associatedWithCompany |
P629
|
FINISHED |
| Object | DHL International GmbH |
E88768
|
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: DHL International GmbH | Statement: [Adrian Dalsey, associatedWithCompany, DHL International GmbH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DHL International GmbH Context triple: [Adrian Dalsey, associatedWithCompany, DHL International GmbH]
-
A.
DHL
DHL is the Dag Hammarskjöld Library, the United Nations’ main research and information resource center located at its headquarters in New York.
-
B.
DHL
chosen
DHL is a global logistics and courier company known for its international express mail, freight transportation, and supply chain management services.
-
C.
Kuehne + Nagel
Kuehne + Nagel is a global logistics and freight forwarding company specializing in sea, air, and contract logistics services.
-
D.
DB Schenker
DB Schenker is a global logistics and freight forwarding company providing land, air, and ocean transport as well as supply chain management services.
-
E.
Geodis
Geodis is a global logistics and supply chain management company providing freight forwarding, contract logistics, and transportation services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1844d7d688190b5badac7a8014f89 |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffeed4e008190b1e8d924b9dc9d37 |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 4:59 a.m.