Triple
T3717822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Window (radar countermeasures) |
E81572
|
entity |
| Predicate | firstMajorUseLocation |
P7528
|
FINISHED |
| Object | Hamburg |
E7419
|
NE FINISHED |
How this triple was built (3 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: Hamburg | Statement: [Window (radar countermeasures), firstMajorUseLocation, Hamburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburg Context triple: [Window (radar countermeasures), firstMajorUseLocation, Hamburg]
-
A.
Hamburg
chosen
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
B.
Bremen
Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
-
C.
Lübeck
Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
-
D.
Bremerhaven
Bremerhaven is a major German port city on the North Sea, known for its maritime industry, shipbuilding, and role as a key hub for trade and logistics.
-
E.
Cologne
Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorUseLocation Context triple: [Window (radar countermeasures), firstMajorUseLocation, Hamburg]
-
A.
firstMajorProductionLocation
Indicates the location where an entity’s first major production or large-scale manufacturing activity took place.
-
B.
firstLocation
Indicates the initial or primary place where an entity is situated, originates, or where an event or relationship begins.
-
C.
locationOfFirstCommercialUse
Indicates the place where something was first used commercially.
-
D.
firstLargeDeploymentLocation
chosen
Indicates the location where something (such as a system, product, or technology) was first deployed at large scale.
-
E.
usedAsLocationIn
Indicates that something serves as the setting or place where another event, action, or situation occurs.
- F. None of above.
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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca984844819087a2f6b20d2f19e7 |
completed | March 8, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4f00a71a881908790c9fccca51a62 |
completed | March 14, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.