Triple
T10908586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merkur (automobile marque) |
E257633
|
entity |
| Predicate | decadeOfPrimaryActivity |
P18555
|
FINISHED |
| Object | 1980s |
—
|
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: 1980s | Statement: [Merkur (automobile marque), decadeOfPrimaryActivity, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decadeOfPrimaryActivity Context triple: [Merkur (automobile marque), decadeOfPrimaryActivity, 1980s]
-
A.
notableYearOfActivity
Indicates the specific year during which an entity was particularly active, prominent, or notable in its activities or impact.
-
B.
dayOfPrimaryActivity
Indicates the specific day on which the primary activity occurs or is scheduled.
-
C.
formerEconomicActivity
Indicates that an entity previously engaged in a specified economic activity but no longer does so.
-
D.
performsPrimarilyIn
Indicates that an entity (such as a performer or group) mainly carries out its performances within a particular location, medium, or context.
-
E.
historicalPeriodOfMajorActivity
chosen
Indicates the historical period during which an entity carried out its most significant or influential activities.
- 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7706824d08190ba894d144cc6b3ba |
completed | April 9, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.